Do I have an “anti-research” personality?What are some options for a graduate student abandoned by Ph. D advisor?PhD supervisor is not willing to co-supervise?Inventors on patent regarding research resultsWhether to change supervisor in UK Masters degree when supervisor is not providing much feedback and says I can change supervisor if I want?How to say good-bye to an unhelpful and undisciplined professor?How to make my work publishable if my supervisor isn’t any help?How to deal with an uncommunicative advisor?Having a retired professor write my letter of recommendation,Is research in private industry more result-oriented than research in academia?Fellow graduate student discusses problems but gives no credit afterwards
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A Note on N!
Do I have an “anti-research” personality?
What are some options for a graduate student abandoned by Ph. D advisor?PhD supervisor is not willing to co-supervise?Inventors on patent regarding research resultsWhether to change supervisor in UK Masters degree when supervisor is not providing much feedback and says I can change supervisor if I want?How to say good-bye to an unhelpful and undisciplined professor?How to make my work publishable if my supervisor isn’t any help?How to deal with an uncommunicative advisor?Having a retired professor write my letter of recommendation,Is research in private industry more result-oriented than research in academia?Fellow graduate student discusses problems but gives no credit afterwards
I am a second year Ph.D. student in a North American university who is mostly working on applied mathematics with a supervisor/advisor/PI. I have been troubled by a pattern of my own behaviour that seems to go against the seemingly correct way to succeed in research and I wonder if I have some sort of an "anti-research" personality.
Here are the problems:
I study whatever is interesting and cool (within a reasonable range of my discipline) and this causes me to lack a solid focus. It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area. For example, while other people's research could be about different types of seahorses, my research would be about seahorses, pipe fish, shrimps...you get the picture.
Since I work in applied math, therefore I often demand more proof of applicability, where my supervisor is totally happy with toy models. He thinks it is completely sufficient for publishing a paper while I think it is fake applied research. This seems to generate some conflict between us and usually I am the one who gives in at the end and do some simulation on these toy models to make him happy - I never care about these problems. Most other people in my field only simulate toy models as well, not really "real-world" applicable in any sense, but hey, it is sure pumping out a lot of papers.
I never collaborate or ask for help from my peers no matter how stuck I become. I often see my colleagues collaborate with each other in the office. A part of me is jealous that they are taking advantage of each other's knowledge, another part of me almost thinks that this is like cheating. I feel that my thesis and my ideas wouldn't be mine if it was interfered or influenced this way. It wouldn't feel authentic
I move on to a completely new topic immediately after I finish my old one. Usually the way I see how other people work is that they try to do something tangentially similar to what they have done before, i.e., blue-tailed seahorses, then yellow-tailed seahorses. I jump to studying pipe fish immediately after I warp up my research on seahorses. I think my advisor must dislike me immensely for starting from scratch after every project.
If a problem seems to have an easy or existing approach that solves it, I find the problem less attractive to the point that I get physically sick from reading about other people's approach. However, a lot of times in research I find that other people would simply adapt other people's method for their own problem and then publish a paper that way. I try to solve it in my own way every time and most of the times it gets to a point where my supervisor intervenes and tell me to do whatever other people are doing. Again, I give in at the end.
I don't even try to follow my advisor's vision of my project. My advisor seems to have his own vision and ulterior goals that are not completely aligned with mine. I think a good PhD student should just listen to him like a father-figure and do whatever I am told. But I don't agree or sometimes don't even care about his specific vision. For example, why should I do a research on the dorsal fin of a seahorse (for your "dorsal fin grant") when I can study pipe fish instead? I understand that he is the one who is funding me, but I also care deeply about my own academic freedom.
Given these habits, am I doomed to fail my PhD? Do I have an anti-research personality?
publications advisor academic-life conflict-of-interest stem
New contributor
add a comment |
I am a second year Ph.D. student in a North American university who is mostly working on applied mathematics with a supervisor/advisor/PI. I have been troubled by a pattern of my own behaviour that seems to go against the seemingly correct way to succeed in research and I wonder if I have some sort of an "anti-research" personality.
Here are the problems:
I study whatever is interesting and cool (within a reasonable range of my discipline) and this causes me to lack a solid focus. It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area. For example, while other people's research could be about different types of seahorses, my research would be about seahorses, pipe fish, shrimps...you get the picture.
Since I work in applied math, therefore I often demand more proof of applicability, where my supervisor is totally happy with toy models. He thinks it is completely sufficient for publishing a paper while I think it is fake applied research. This seems to generate some conflict between us and usually I am the one who gives in at the end and do some simulation on these toy models to make him happy - I never care about these problems. Most other people in my field only simulate toy models as well, not really "real-world" applicable in any sense, but hey, it is sure pumping out a lot of papers.
I never collaborate or ask for help from my peers no matter how stuck I become. I often see my colleagues collaborate with each other in the office. A part of me is jealous that they are taking advantage of each other's knowledge, another part of me almost thinks that this is like cheating. I feel that my thesis and my ideas wouldn't be mine if it was interfered or influenced this way. It wouldn't feel authentic
I move on to a completely new topic immediately after I finish my old one. Usually the way I see how other people work is that they try to do something tangentially similar to what they have done before, i.e., blue-tailed seahorses, then yellow-tailed seahorses. I jump to studying pipe fish immediately after I warp up my research on seahorses. I think my advisor must dislike me immensely for starting from scratch after every project.
If a problem seems to have an easy or existing approach that solves it, I find the problem less attractive to the point that I get physically sick from reading about other people's approach. However, a lot of times in research I find that other people would simply adapt other people's method for their own problem and then publish a paper that way. I try to solve it in my own way every time and most of the times it gets to a point where my supervisor intervenes and tell me to do whatever other people are doing. Again, I give in at the end.
I don't even try to follow my advisor's vision of my project. My advisor seems to have his own vision and ulterior goals that are not completely aligned with mine. I think a good PhD student should just listen to him like a father-figure and do whatever I am told. But I don't agree or sometimes don't even care about his specific vision. For example, why should I do a research on the dorsal fin of a seahorse (for your "dorsal fin grant") when I can study pipe fish instead? I understand that he is the one who is funding me, but I also care deeply about my own academic freedom.
Given these habits, am I doomed to fail my PhD? Do I have an anti-research personality?
publications advisor academic-life conflict-of-interest stem
New contributor
19
"I get physically sick from reading about other people's approach." This is a pretty striking thing to say and suggests something deeper is going on. You come across as rather hostile to people in general, which is going to make things tricky in any career.
– Noah Snyder
9 hours ago
some of that seems like general workplace/professionalism issues. Have your work been hurt yet? What do you want to achieve in life?
– aaaaaa
8 hours ago
11
Honestly? It sounds like you prefer "problem-solving" to research and would probably be happier in industry than academia.
– Elizabeth Henning
6 hours ago
2
"1. ... It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area." I can't speak for what type of maths you're doing, but I do pure maths (discrete probability), and this is not what happens. Sure, I specialise in a particular field, but it's not like I just do one thing the whole time. My supervisor has worked on stuff to do with Brownian motion, BitTorrent algorithms, percolation, random walks, random graphs -- and I would say her research is quite narrow compared with some!
– Sam T
3 hours ago
Maybe you actually have got a personality which is averse to some parts of how research is practiced at certain institutions ;) but if you pay attention to stay diplomatic, that does absolutely not mean you are doomed to fail. (Please remember, there is a large social component in doing a PhD, no matter what the technical regulations say.)
– jvb
2 hours ago
add a comment |
I am a second year Ph.D. student in a North American university who is mostly working on applied mathematics with a supervisor/advisor/PI. I have been troubled by a pattern of my own behaviour that seems to go against the seemingly correct way to succeed in research and I wonder if I have some sort of an "anti-research" personality.
Here are the problems:
I study whatever is interesting and cool (within a reasonable range of my discipline) and this causes me to lack a solid focus. It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area. For example, while other people's research could be about different types of seahorses, my research would be about seahorses, pipe fish, shrimps...you get the picture.
Since I work in applied math, therefore I often demand more proof of applicability, where my supervisor is totally happy with toy models. He thinks it is completely sufficient for publishing a paper while I think it is fake applied research. This seems to generate some conflict between us and usually I am the one who gives in at the end and do some simulation on these toy models to make him happy - I never care about these problems. Most other people in my field only simulate toy models as well, not really "real-world" applicable in any sense, but hey, it is sure pumping out a lot of papers.
I never collaborate or ask for help from my peers no matter how stuck I become. I often see my colleagues collaborate with each other in the office. A part of me is jealous that they are taking advantage of each other's knowledge, another part of me almost thinks that this is like cheating. I feel that my thesis and my ideas wouldn't be mine if it was interfered or influenced this way. It wouldn't feel authentic
I move on to a completely new topic immediately after I finish my old one. Usually the way I see how other people work is that they try to do something tangentially similar to what they have done before, i.e., blue-tailed seahorses, then yellow-tailed seahorses. I jump to studying pipe fish immediately after I warp up my research on seahorses. I think my advisor must dislike me immensely for starting from scratch after every project.
If a problem seems to have an easy or existing approach that solves it, I find the problem less attractive to the point that I get physically sick from reading about other people's approach. However, a lot of times in research I find that other people would simply adapt other people's method for their own problem and then publish a paper that way. I try to solve it in my own way every time and most of the times it gets to a point where my supervisor intervenes and tell me to do whatever other people are doing. Again, I give in at the end.
I don't even try to follow my advisor's vision of my project. My advisor seems to have his own vision and ulterior goals that are not completely aligned with mine. I think a good PhD student should just listen to him like a father-figure and do whatever I am told. But I don't agree or sometimes don't even care about his specific vision. For example, why should I do a research on the dorsal fin of a seahorse (for your "dorsal fin grant") when I can study pipe fish instead? I understand that he is the one who is funding me, but I also care deeply about my own academic freedom.
Given these habits, am I doomed to fail my PhD? Do I have an anti-research personality?
publications advisor academic-life conflict-of-interest stem
New contributor
I am a second year Ph.D. student in a North American university who is mostly working on applied mathematics with a supervisor/advisor/PI. I have been troubled by a pattern of my own behaviour that seems to go against the seemingly correct way to succeed in research and I wonder if I have some sort of an "anti-research" personality.
Here are the problems:
I study whatever is interesting and cool (within a reasonable range of my discipline) and this causes me to lack a solid focus. It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area. For example, while other people's research could be about different types of seahorses, my research would be about seahorses, pipe fish, shrimps...you get the picture.
Since I work in applied math, therefore I often demand more proof of applicability, where my supervisor is totally happy with toy models. He thinks it is completely sufficient for publishing a paper while I think it is fake applied research. This seems to generate some conflict between us and usually I am the one who gives in at the end and do some simulation on these toy models to make him happy - I never care about these problems. Most other people in my field only simulate toy models as well, not really "real-world" applicable in any sense, but hey, it is sure pumping out a lot of papers.
I never collaborate or ask for help from my peers no matter how stuck I become. I often see my colleagues collaborate with each other in the office. A part of me is jealous that they are taking advantage of each other's knowledge, another part of me almost thinks that this is like cheating. I feel that my thesis and my ideas wouldn't be mine if it was interfered or influenced this way. It wouldn't feel authentic
I move on to a completely new topic immediately after I finish my old one. Usually the way I see how other people work is that they try to do something tangentially similar to what they have done before, i.e., blue-tailed seahorses, then yellow-tailed seahorses. I jump to studying pipe fish immediately after I warp up my research on seahorses. I think my advisor must dislike me immensely for starting from scratch after every project.
If a problem seems to have an easy or existing approach that solves it, I find the problem less attractive to the point that I get physically sick from reading about other people's approach. However, a lot of times in research I find that other people would simply adapt other people's method for their own problem and then publish a paper that way. I try to solve it in my own way every time and most of the times it gets to a point where my supervisor intervenes and tell me to do whatever other people are doing. Again, I give in at the end.
I don't even try to follow my advisor's vision of my project. My advisor seems to have his own vision and ulterior goals that are not completely aligned with mine. I think a good PhD student should just listen to him like a father-figure and do whatever I am told. But I don't agree or sometimes don't even care about his specific vision. For example, why should I do a research on the dorsal fin of a seahorse (for your "dorsal fin grant") when I can study pipe fish instead? I understand that he is the one who is funding me, but I also care deeply about my own academic freedom.
Given these habits, am I doomed to fail my PhD? Do I have an anti-research personality?
publications advisor academic-life conflict-of-interest stem
publications advisor academic-life conflict-of-interest stem
New contributor
New contributor
New contributor
asked 22 hours ago
Squaring the Circle is EasySquaring the Circle is Easy
914
914
New contributor
New contributor
19
"I get physically sick from reading about other people's approach." This is a pretty striking thing to say and suggests something deeper is going on. You come across as rather hostile to people in general, which is going to make things tricky in any career.
– Noah Snyder
9 hours ago
some of that seems like general workplace/professionalism issues. Have your work been hurt yet? What do you want to achieve in life?
– aaaaaa
8 hours ago
11
Honestly? It sounds like you prefer "problem-solving" to research and would probably be happier in industry than academia.
– Elizabeth Henning
6 hours ago
2
"1. ... It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area." I can't speak for what type of maths you're doing, but I do pure maths (discrete probability), and this is not what happens. Sure, I specialise in a particular field, but it's not like I just do one thing the whole time. My supervisor has worked on stuff to do with Brownian motion, BitTorrent algorithms, percolation, random walks, random graphs -- and I would say her research is quite narrow compared with some!
– Sam T
3 hours ago
Maybe you actually have got a personality which is averse to some parts of how research is practiced at certain institutions ;) but if you pay attention to stay diplomatic, that does absolutely not mean you are doomed to fail. (Please remember, there is a large social component in doing a PhD, no matter what the technical regulations say.)
– jvb
2 hours ago
add a comment |
19
"I get physically sick from reading about other people's approach." This is a pretty striking thing to say and suggests something deeper is going on. You come across as rather hostile to people in general, which is going to make things tricky in any career.
– Noah Snyder
9 hours ago
some of that seems like general workplace/professionalism issues. Have your work been hurt yet? What do you want to achieve in life?
– aaaaaa
8 hours ago
11
Honestly? It sounds like you prefer "problem-solving" to research and would probably be happier in industry than academia.
– Elizabeth Henning
6 hours ago
2
"1. ... It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area." I can't speak for what type of maths you're doing, but I do pure maths (discrete probability), and this is not what happens. Sure, I specialise in a particular field, but it's not like I just do one thing the whole time. My supervisor has worked on stuff to do with Brownian motion, BitTorrent algorithms, percolation, random walks, random graphs -- and I would say her research is quite narrow compared with some!
– Sam T
3 hours ago
Maybe you actually have got a personality which is averse to some parts of how research is practiced at certain institutions ;) but if you pay attention to stay diplomatic, that does absolutely not mean you are doomed to fail. (Please remember, there is a large social component in doing a PhD, no matter what the technical regulations say.)
– jvb
2 hours ago
19
19
"I get physically sick from reading about other people's approach." This is a pretty striking thing to say and suggests something deeper is going on. You come across as rather hostile to people in general, which is going to make things tricky in any career.
– Noah Snyder
9 hours ago
"I get physically sick from reading about other people's approach." This is a pretty striking thing to say and suggests something deeper is going on. You come across as rather hostile to people in general, which is going to make things tricky in any career.
– Noah Snyder
9 hours ago
some of that seems like general workplace/professionalism issues. Have your work been hurt yet? What do you want to achieve in life?
– aaaaaa
8 hours ago
some of that seems like general workplace/professionalism issues. Have your work been hurt yet? What do you want to achieve in life?
– aaaaaa
8 hours ago
11
11
Honestly? It sounds like you prefer "problem-solving" to research and would probably be happier in industry than academia.
– Elizabeth Henning
6 hours ago
Honestly? It sounds like you prefer "problem-solving" to research and would probably be happier in industry than academia.
– Elizabeth Henning
6 hours ago
2
2
"1. ... It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area." I can't speak for what type of maths you're doing, but I do pure maths (discrete probability), and this is not what happens. Sure, I specialise in a particular field, but it's not like I just do one thing the whole time. My supervisor has worked on stuff to do with Brownian motion, BitTorrent algorithms, percolation, random walks, random graphs -- and I would say her research is quite narrow compared with some!
– Sam T
3 hours ago
"1. ... It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area." I can't speak for what type of maths you're doing, but I do pure maths (discrete probability), and this is not what happens. Sure, I specialise in a particular field, but it's not like I just do one thing the whole time. My supervisor has worked on stuff to do with Brownian motion, BitTorrent algorithms, percolation, random walks, random graphs -- and I would say her research is quite narrow compared with some!
– Sam T
3 hours ago
Maybe you actually have got a personality which is averse to some parts of how research is practiced at certain institutions ;) but if you pay attention to stay diplomatic, that does absolutely not mean you are doomed to fail. (Please remember, there is a large social component in doing a PhD, no matter what the technical regulations say.)
– jvb
2 hours ago
Maybe you actually have got a personality which is averse to some parts of how research is practiced at certain institutions ;) but if you pay attention to stay diplomatic, that does absolutely not mean you are doomed to fail. (Please remember, there is a large social component in doing a PhD, no matter what the technical regulations say.)
– jvb
2 hours ago
add a comment |
4 Answers
4
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Having a broad set of interests and knowledge is fine, and can lead to some 'outside of the box' solutions. Yes, you will find periods where anything else is more interesting than your PhD work, irrespective of how interesting your PhD work actually is. You'll find that as you come closer to the end of your PhD, your concentration on the problem at hand will sharpen, and while a PhD deadline isn't quite as good at sharpening a mind as an impending duel, you probably will find your ability to concentrate improve as the ending comes into sight.
Furthermore, don't assume what you're researching your PhD on is what you'll be doing for the rest of your life. Having a wide set of skills and a shallow knowledge of many things will often help you out when you (most likely) realise you don't have the desire to become an academic, and need to search for a different job (which, let's face it, given your background means probably going in to Data Science)
I don't know too much about the culture of applied math to make an informed comment on this, but in general, finding a good real-world application of a concept, and carrying it out, is difficult. It can involve a lot of time mucking around with real world datasets, which are often messy. You have an obligation to show that your results and methods are useful, but to what degree is up to taste, and I don't think is an issue with any kind of 'anti-research' personality.
This sort of thinking is by far your most serious problem. If asking fellow students for help and collaborating is cheating, then so is using Stackexchange or reading from a textbook. Modern civilisation rests on the ability to record our thoughts so every human doesn't have to derive all the rules from scratch. There is nothing dishonourable about asking for help. If someone gives you helpful ideas, thank them in your thesis. Even if they do clever novel work on your problem, you still have to at the very least understand it and synthesize it into your own work.
There is a certain kind of person who is reluctant to ask questions. I would count myself as one. If you feel uncomfortable doing do, I recommend working on that skill until you do feel more comfortable. Stackexchange is the perfect place for that - even if it isn't a question about anything to do with your research.
This behaviour is fine. One can get a certain fatigue when working on certain projects for a while.
& 6. It does really seem like you have a need to derive and understand everything from its foundations. In real life, this is rarely necessary.
I did a PhD in organic chemistry. After that, I decided I didn't like chemistry anymore and went on to be a Data Scientist. At first, I would spend a lot of time trying to mathematically understand the techniques I was using, and I wouldn't feel comfortable using them if I didn't understand the underlying linear algebra. Then I slowly got more comfortable using techniques whose underlying mechanics I don't understand. We by and large don't understand the inner workings of a car or computer. We do know, roughly, its outputs when given certain inputs. The inner workings are a problem already solved by someone else.
As you grow older and read more, you'll be continuously struck by the sheer quantity of stuff out there that people have figured out. The sheer amount of knowledge that goes into, say, building an aeroplane or a computer game or a treatment plan for a specific disease or a skyscraper or a hadron collider. Letting go of the need of having to understand all aspects of a certain thing is an important skill. Practice triage with the information you receive and the problems you encounter. Trust in the expertise of others who have come before you. Know when to expend your brainpower, and know when to conserve it.
So in summary, apart from issue 3, I don't think you have any significant "anti-research' personality issues.
New contributor
10
To add to issue 3, the academic world relies heavily on networking and collaborations are a key element of that. Even if it is just a short chat about common research interests over a cup of coffee, people are much more likely to remember you and your research if you work with them. And if no one knows you, your papers are far less likely to be read and people will far less likely consider you when they have open positions to fill or grants to give.
– mlk
17 hours ago
7
Agree. To further point 3, I find it helpful during a brainstorming period to sit and talk through the problem with someone else. Having to formulate the problem in words understood by someone else helps me actually understand it too. Much like you don’t really understand your results until you write the paper such that someone else can too.
– Jon Custer
11 hours ago
add a comment |
Let me preface my answer by challenging an unwritten assumption of yours: that you have a fixed "personality" which is hampering your potential as a researcher. This simply is false. Nobody is born a good researcher. It takes hard work to become one. Sure, some people have predispositions that help them. But in the end, you cannot avoid doing the work, including work on yourself.
You have discovered that you lack certain skills, or that your aptitude for them is currently insufficient. Blaming this on your personality as something that you cannot change is lazy. It is up to you to improve in these areas. If you refuse, then you are to blame, not some god-given "personality" that was forced upon you.
I will now answer point by point, but if you are honest with yourself, you already know what I am going to say.
- There is a common saying: "jack of all trades, master of none". In math, you are studying concepts that other people have been studying and refining for decades if not centuries. You are not going to master them by studying them for a few months and moving on to the next target. You are now at the bleeding edge of research, and it takes hard work to get up to speed. Your PhD is the occasion that you get to demonstrate that you are able to become a true expert at something and make improvements to the state of the art. It is unlikely that you will manage that by working on something for six months and moving on to something else afterwards.
However, getting interested in other things is not just fine, it is mandatory if you want to have a successful career after your PhD. - You seem to be confused about what applied math really is. Math that you actually apply in the real world is usually called engineering. It is a one-in-a-million occurrence for something in applied math to find a real-world application. But since you don't know in advance what will work, you have to start somewhere. Toy models are where it's at. You start with something simple. Maybe it works. Maybe you realize it's more complicated than what it appeared (the most common occurrence). Maybe it turns out to be useless. You don't know, because you are not an oracle.
- There is nothing "fake" about getting influenced by others. Here is another common saying: in academia, we are standing on the shoulders of giants. You are reading papers, aren't you? You didn't discovered all of applied math by yourself from scratch, did you? Aren't these papers influencing your research, your way of thinking? Have you never read something and thought, "hey, I never thought about it like that", or "wow, this unrelated topic gave me ideas for my current research"? The difference with face to face conversations is that it's happening in real time. That's basically it.
And here's another saying, as I like them: alone you go faster, together you go farther. Other people have a different way of thinking, a different skillset, a different knowledge of the literature, different ideas. By pooling your resources together, you will probably be able to solve bigger problems than if you were on your own.
Finally, collaborating is just fun. Try it and you will see. - See #1. If you are happy with making tiny contributions to the state of the art all the time, good for you. (This is especially at odds with your apparent disgust for people who "pump out" papers, but whatever.) Meanwhile, someone will study seahorses for ten years and revolutionize the field by realizing that seahorses are aquatic poneys, rendering most of your previous research mostly useless.
- Solving things on your own is fine and valuable. Being able to use other people's ideas to solve your problem more quickly is an extremely valuable skill, however. While you will be reinventing the wheel, others will go around the world in a plane.
- This is something between you and your advisor. As a PhD student, you are supposed to transition from supervised research to autonomous research. If you really feel this way, talk about it openly with your supervisor. Maybe you will be surprised. Maybe your supervisor even thinks that you are not ready for unsupervised research because of your other points (unability to focus, to collaborate, to make use of other people's ideas and applying them to your own problem…) and this is why he is still asking you to work on something where he can directly help you and direct you in your research, instead of letting you work on something with less direction and help.
So yes, if you continue with the mindset that there are certain things about yourself that you cannot improve due to your "personality", you will have a hard time, in academia and elsewhere. You will continue to give up at the first obstacle and never amount to much. And you can continue to think that nature, your personality, your upbringing… is to the culprit, in the end, you are the one who has to live with the consequences.
New contributor
2
Just adding some nuance to your statement that "Nobody is born a good researcher.". I think it's the opposite: everyone is born a researcher. Observing babies shows that they are excellent experimental scientists: they will keep trying to do whatever it is they are interested in until they figure it out, then move on to the next interesting thing, etc. It's too bad that we lose this ability at some point in late childhood and have to learn it again later on if we want to become good at doing research.
– Guillaume
7 hours ago
1
I'm on @user108161 's side on this: I guess the "natural" thing in everyday life is jumping to conclusions - that's the way selection works: most of the time, our conclusions and preconceptions either hold or are at least (computationally) cheap. Handling (understanding, modelling) counterintuitive relations usually needs some advanced training.
– jvb
2 hours ago
add a comment |
Short answer to complement other longer good ones here.
You do seem really to care about the seahorses of all colors, and the pipefish and the shrimp. So focus now on learning whatever you can in your current environment. Continue reading stuff that's not directly applicable. Do collaborate. Finish your PhD (toy models are sometimes good places to start). Then look for a postdoc with someone whose philosophy and style better match yours. When you run your own lab, look for students like you.
add a comment |
The only problem is the issue you have about networking/collaboration. There are different styles of research and approaches, not everyone "processes" things in the same way. Having a large survey level knowledge of the field is actually very important and its a skill that often some people don't have. I recommend to acquire professional level skills on something practical and useful across fields (programming, probability, numerical methods) and then you can always apply that skillset to different problems.
add a comment |
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Having a broad set of interests and knowledge is fine, and can lead to some 'outside of the box' solutions. Yes, you will find periods where anything else is more interesting than your PhD work, irrespective of how interesting your PhD work actually is. You'll find that as you come closer to the end of your PhD, your concentration on the problem at hand will sharpen, and while a PhD deadline isn't quite as good at sharpening a mind as an impending duel, you probably will find your ability to concentrate improve as the ending comes into sight.
Furthermore, don't assume what you're researching your PhD on is what you'll be doing for the rest of your life. Having a wide set of skills and a shallow knowledge of many things will often help you out when you (most likely) realise you don't have the desire to become an academic, and need to search for a different job (which, let's face it, given your background means probably going in to Data Science)
I don't know too much about the culture of applied math to make an informed comment on this, but in general, finding a good real-world application of a concept, and carrying it out, is difficult. It can involve a lot of time mucking around with real world datasets, which are often messy. You have an obligation to show that your results and methods are useful, but to what degree is up to taste, and I don't think is an issue with any kind of 'anti-research' personality.
This sort of thinking is by far your most serious problem. If asking fellow students for help and collaborating is cheating, then so is using Stackexchange or reading from a textbook. Modern civilisation rests on the ability to record our thoughts so every human doesn't have to derive all the rules from scratch. There is nothing dishonourable about asking for help. If someone gives you helpful ideas, thank them in your thesis. Even if they do clever novel work on your problem, you still have to at the very least understand it and synthesize it into your own work.
There is a certain kind of person who is reluctant to ask questions. I would count myself as one. If you feel uncomfortable doing do, I recommend working on that skill until you do feel more comfortable. Stackexchange is the perfect place for that - even if it isn't a question about anything to do with your research.
This behaviour is fine. One can get a certain fatigue when working on certain projects for a while.
& 6. It does really seem like you have a need to derive and understand everything from its foundations. In real life, this is rarely necessary.
I did a PhD in organic chemistry. After that, I decided I didn't like chemistry anymore and went on to be a Data Scientist. At first, I would spend a lot of time trying to mathematically understand the techniques I was using, and I wouldn't feel comfortable using them if I didn't understand the underlying linear algebra. Then I slowly got more comfortable using techniques whose underlying mechanics I don't understand. We by and large don't understand the inner workings of a car or computer. We do know, roughly, its outputs when given certain inputs. The inner workings are a problem already solved by someone else.
As you grow older and read more, you'll be continuously struck by the sheer quantity of stuff out there that people have figured out. The sheer amount of knowledge that goes into, say, building an aeroplane or a computer game or a treatment plan for a specific disease or a skyscraper or a hadron collider. Letting go of the need of having to understand all aspects of a certain thing is an important skill. Practice triage with the information you receive and the problems you encounter. Trust in the expertise of others who have come before you. Know when to expend your brainpower, and know when to conserve it.
So in summary, apart from issue 3, I don't think you have any significant "anti-research' personality issues.
New contributor
10
To add to issue 3, the academic world relies heavily on networking and collaborations are a key element of that. Even if it is just a short chat about common research interests over a cup of coffee, people are much more likely to remember you and your research if you work with them. And if no one knows you, your papers are far less likely to be read and people will far less likely consider you when they have open positions to fill or grants to give.
– mlk
17 hours ago
7
Agree. To further point 3, I find it helpful during a brainstorming period to sit and talk through the problem with someone else. Having to formulate the problem in words understood by someone else helps me actually understand it too. Much like you don’t really understand your results until you write the paper such that someone else can too.
– Jon Custer
11 hours ago
add a comment |
Having a broad set of interests and knowledge is fine, and can lead to some 'outside of the box' solutions. Yes, you will find periods where anything else is more interesting than your PhD work, irrespective of how interesting your PhD work actually is. You'll find that as you come closer to the end of your PhD, your concentration on the problem at hand will sharpen, and while a PhD deadline isn't quite as good at sharpening a mind as an impending duel, you probably will find your ability to concentrate improve as the ending comes into sight.
Furthermore, don't assume what you're researching your PhD on is what you'll be doing for the rest of your life. Having a wide set of skills and a shallow knowledge of many things will often help you out when you (most likely) realise you don't have the desire to become an academic, and need to search for a different job (which, let's face it, given your background means probably going in to Data Science)
I don't know too much about the culture of applied math to make an informed comment on this, but in general, finding a good real-world application of a concept, and carrying it out, is difficult. It can involve a lot of time mucking around with real world datasets, which are often messy. You have an obligation to show that your results and methods are useful, but to what degree is up to taste, and I don't think is an issue with any kind of 'anti-research' personality.
This sort of thinking is by far your most serious problem. If asking fellow students for help and collaborating is cheating, then so is using Stackexchange or reading from a textbook. Modern civilisation rests on the ability to record our thoughts so every human doesn't have to derive all the rules from scratch. There is nothing dishonourable about asking for help. If someone gives you helpful ideas, thank them in your thesis. Even if they do clever novel work on your problem, you still have to at the very least understand it and synthesize it into your own work.
There is a certain kind of person who is reluctant to ask questions. I would count myself as one. If you feel uncomfortable doing do, I recommend working on that skill until you do feel more comfortable. Stackexchange is the perfect place for that - even if it isn't a question about anything to do with your research.
This behaviour is fine. One can get a certain fatigue when working on certain projects for a while.
& 6. It does really seem like you have a need to derive and understand everything from its foundations. In real life, this is rarely necessary.
I did a PhD in organic chemistry. After that, I decided I didn't like chemistry anymore and went on to be a Data Scientist. At first, I would spend a lot of time trying to mathematically understand the techniques I was using, and I wouldn't feel comfortable using them if I didn't understand the underlying linear algebra. Then I slowly got more comfortable using techniques whose underlying mechanics I don't understand. We by and large don't understand the inner workings of a car or computer. We do know, roughly, its outputs when given certain inputs. The inner workings are a problem already solved by someone else.
As you grow older and read more, you'll be continuously struck by the sheer quantity of stuff out there that people have figured out. The sheer amount of knowledge that goes into, say, building an aeroplane or a computer game or a treatment plan for a specific disease or a skyscraper or a hadron collider. Letting go of the need of having to understand all aspects of a certain thing is an important skill. Practice triage with the information you receive and the problems you encounter. Trust in the expertise of others who have come before you. Know when to expend your brainpower, and know when to conserve it.
So in summary, apart from issue 3, I don't think you have any significant "anti-research' personality issues.
New contributor
10
To add to issue 3, the academic world relies heavily on networking and collaborations are a key element of that. Even if it is just a short chat about common research interests over a cup of coffee, people are much more likely to remember you and your research if you work with them. And if no one knows you, your papers are far less likely to be read and people will far less likely consider you when they have open positions to fill or grants to give.
– mlk
17 hours ago
7
Agree. To further point 3, I find it helpful during a brainstorming period to sit and talk through the problem with someone else. Having to formulate the problem in words understood by someone else helps me actually understand it too. Much like you don’t really understand your results until you write the paper such that someone else can too.
– Jon Custer
11 hours ago
add a comment |
Having a broad set of interests and knowledge is fine, and can lead to some 'outside of the box' solutions. Yes, you will find periods where anything else is more interesting than your PhD work, irrespective of how interesting your PhD work actually is. You'll find that as you come closer to the end of your PhD, your concentration on the problem at hand will sharpen, and while a PhD deadline isn't quite as good at sharpening a mind as an impending duel, you probably will find your ability to concentrate improve as the ending comes into sight.
Furthermore, don't assume what you're researching your PhD on is what you'll be doing for the rest of your life. Having a wide set of skills and a shallow knowledge of many things will often help you out when you (most likely) realise you don't have the desire to become an academic, and need to search for a different job (which, let's face it, given your background means probably going in to Data Science)
I don't know too much about the culture of applied math to make an informed comment on this, but in general, finding a good real-world application of a concept, and carrying it out, is difficult. It can involve a lot of time mucking around with real world datasets, which are often messy. You have an obligation to show that your results and methods are useful, but to what degree is up to taste, and I don't think is an issue with any kind of 'anti-research' personality.
This sort of thinking is by far your most serious problem. If asking fellow students for help and collaborating is cheating, then so is using Stackexchange or reading from a textbook. Modern civilisation rests on the ability to record our thoughts so every human doesn't have to derive all the rules from scratch. There is nothing dishonourable about asking for help. If someone gives you helpful ideas, thank them in your thesis. Even if they do clever novel work on your problem, you still have to at the very least understand it and synthesize it into your own work.
There is a certain kind of person who is reluctant to ask questions. I would count myself as one. If you feel uncomfortable doing do, I recommend working on that skill until you do feel more comfortable. Stackexchange is the perfect place for that - even if it isn't a question about anything to do with your research.
This behaviour is fine. One can get a certain fatigue when working on certain projects for a while.
& 6. It does really seem like you have a need to derive and understand everything from its foundations. In real life, this is rarely necessary.
I did a PhD in organic chemistry. After that, I decided I didn't like chemistry anymore and went on to be a Data Scientist. At first, I would spend a lot of time trying to mathematically understand the techniques I was using, and I wouldn't feel comfortable using them if I didn't understand the underlying linear algebra. Then I slowly got more comfortable using techniques whose underlying mechanics I don't understand. We by and large don't understand the inner workings of a car or computer. We do know, roughly, its outputs when given certain inputs. The inner workings are a problem already solved by someone else.
As you grow older and read more, you'll be continuously struck by the sheer quantity of stuff out there that people have figured out. The sheer amount of knowledge that goes into, say, building an aeroplane or a computer game or a treatment plan for a specific disease or a skyscraper or a hadron collider. Letting go of the need of having to understand all aspects of a certain thing is an important skill. Practice triage with the information you receive and the problems you encounter. Trust in the expertise of others who have come before you. Know when to expend your brainpower, and know when to conserve it.
So in summary, apart from issue 3, I don't think you have any significant "anti-research' personality issues.
New contributor
Having a broad set of interests and knowledge is fine, and can lead to some 'outside of the box' solutions. Yes, you will find periods where anything else is more interesting than your PhD work, irrespective of how interesting your PhD work actually is. You'll find that as you come closer to the end of your PhD, your concentration on the problem at hand will sharpen, and while a PhD deadline isn't quite as good at sharpening a mind as an impending duel, you probably will find your ability to concentrate improve as the ending comes into sight.
Furthermore, don't assume what you're researching your PhD on is what you'll be doing for the rest of your life. Having a wide set of skills and a shallow knowledge of many things will often help you out when you (most likely) realise you don't have the desire to become an academic, and need to search for a different job (which, let's face it, given your background means probably going in to Data Science)
I don't know too much about the culture of applied math to make an informed comment on this, but in general, finding a good real-world application of a concept, and carrying it out, is difficult. It can involve a lot of time mucking around with real world datasets, which are often messy. You have an obligation to show that your results and methods are useful, but to what degree is up to taste, and I don't think is an issue with any kind of 'anti-research' personality.
This sort of thinking is by far your most serious problem. If asking fellow students for help and collaborating is cheating, then so is using Stackexchange or reading from a textbook. Modern civilisation rests on the ability to record our thoughts so every human doesn't have to derive all the rules from scratch. There is nothing dishonourable about asking for help. If someone gives you helpful ideas, thank them in your thesis. Even if they do clever novel work on your problem, you still have to at the very least understand it and synthesize it into your own work.
There is a certain kind of person who is reluctant to ask questions. I would count myself as one. If you feel uncomfortable doing do, I recommend working on that skill until you do feel more comfortable. Stackexchange is the perfect place for that - even if it isn't a question about anything to do with your research.
This behaviour is fine. One can get a certain fatigue when working on certain projects for a while.
& 6. It does really seem like you have a need to derive and understand everything from its foundations. In real life, this is rarely necessary.
I did a PhD in organic chemistry. After that, I decided I didn't like chemistry anymore and went on to be a Data Scientist. At first, I would spend a lot of time trying to mathematically understand the techniques I was using, and I wouldn't feel comfortable using them if I didn't understand the underlying linear algebra. Then I slowly got more comfortable using techniques whose underlying mechanics I don't understand. We by and large don't understand the inner workings of a car or computer. We do know, roughly, its outputs when given certain inputs. The inner workings are a problem already solved by someone else.
As you grow older and read more, you'll be continuously struck by the sheer quantity of stuff out there that people have figured out. The sheer amount of knowledge that goes into, say, building an aeroplane or a computer game or a treatment plan for a specific disease or a skyscraper or a hadron collider. Letting go of the need of having to understand all aspects of a certain thing is an important skill. Practice triage with the information you receive and the problems you encounter. Trust in the expertise of others who have come before you. Know when to expend your brainpower, and know when to conserve it.
So in summary, apart from issue 3, I don't think you have any significant "anti-research' personality issues.
New contributor
New contributor
answered 19 hours ago
IngolifsIngolifs
30115
30115
New contributor
New contributor
10
To add to issue 3, the academic world relies heavily on networking and collaborations are a key element of that. Even if it is just a short chat about common research interests over a cup of coffee, people are much more likely to remember you and your research if you work with them. And if no one knows you, your papers are far less likely to be read and people will far less likely consider you when they have open positions to fill or grants to give.
– mlk
17 hours ago
7
Agree. To further point 3, I find it helpful during a brainstorming period to sit and talk through the problem with someone else. Having to formulate the problem in words understood by someone else helps me actually understand it too. Much like you don’t really understand your results until you write the paper such that someone else can too.
– Jon Custer
11 hours ago
add a comment |
10
To add to issue 3, the academic world relies heavily on networking and collaborations are a key element of that. Even if it is just a short chat about common research interests over a cup of coffee, people are much more likely to remember you and your research if you work with them. And if no one knows you, your papers are far less likely to be read and people will far less likely consider you when they have open positions to fill or grants to give.
– mlk
17 hours ago
7
Agree. To further point 3, I find it helpful during a brainstorming period to sit and talk through the problem with someone else. Having to formulate the problem in words understood by someone else helps me actually understand it too. Much like you don’t really understand your results until you write the paper such that someone else can too.
– Jon Custer
11 hours ago
10
10
To add to issue 3, the academic world relies heavily on networking and collaborations are a key element of that. Even if it is just a short chat about common research interests over a cup of coffee, people are much more likely to remember you and your research if you work with them. And if no one knows you, your papers are far less likely to be read and people will far less likely consider you when they have open positions to fill or grants to give.
– mlk
17 hours ago
To add to issue 3, the academic world relies heavily on networking and collaborations are a key element of that. Even if it is just a short chat about common research interests over a cup of coffee, people are much more likely to remember you and your research if you work with them. And if no one knows you, your papers are far less likely to be read and people will far less likely consider you when they have open positions to fill or grants to give.
– mlk
17 hours ago
7
7
Agree. To further point 3, I find it helpful during a brainstorming period to sit and talk through the problem with someone else. Having to formulate the problem in words understood by someone else helps me actually understand it too. Much like you don’t really understand your results until you write the paper such that someone else can too.
– Jon Custer
11 hours ago
Agree. To further point 3, I find it helpful during a brainstorming period to sit and talk through the problem with someone else. Having to formulate the problem in words understood by someone else helps me actually understand it too. Much like you don’t really understand your results until you write the paper such that someone else can too.
– Jon Custer
11 hours ago
add a comment |
Let me preface my answer by challenging an unwritten assumption of yours: that you have a fixed "personality" which is hampering your potential as a researcher. This simply is false. Nobody is born a good researcher. It takes hard work to become one. Sure, some people have predispositions that help them. But in the end, you cannot avoid doing the work, including work on yourself.
You have discovered that you lack certain skills, or that your aptitude for them is currently insufficient. Blaming this on your personality as something that you cannot change is lazy. It is up to you to improve in these areas. If you refuse, then you are to blame, not some god-given "personality" that was forced upon you.
I will now answer point by point, but if you are honest with yourself, you already know what I am going to say.
- There is a common saying: "jack of all trades, master of none". In math, you are studying concepts that other people have been studying and refining for decades if not centuries. You are not going to master them by studying them for a few months and moving on to the next target. You are now at the bleeding edge of research, and it takes hard work to get up to speed. Your PhD is the occasion that you get to demonstrate that you are able to become a true expert at something and make improvements to the state of the art. It is unlikely that you will manage that by working on something for six months and moving on to something else afterwards.
However, getting interested in other things is not just fine, it is mandatory if you want to have a successful career after your PhD. - You seem to be confused about what applied math really is. Math that you actually apply in the real world is usually called engineering. It is a one-in-a-million occurrence for something in applied math to find a real-world application. But since you don't know in advance what will work, you have to start somewhere. Toy models are where it's at. You start with something simple. Maybe it works. Maybe you realize it's more complicated than what it appeared (the most common occurrence). Maybe it turns out to be useless. You don't know, because you are not an oracle.
- There is nothing "fake" about getting influenced by others. Here is another common saying: in academia, we are standing on the shoulders of giants. You are reading papers, aren't you? You didn't discovered all of applied math by yourself from scratch, did you? Aren't these papers influencing your research, your way of thinking? Have you never read something and thought, "hey, I never thought about it like that", or "wow, this unrelated topic gave me ideas for my current research"? The difference with face to face conversations is that it's happening in real time. That's basically it.
And here's another saying, as I like them: alone you go faster, together you go farther. Other people have a different way of thinking, a different skillset, a different knowledge of the literature, different ideas. By pooling your resources together, you will probably be able to solve bigger problems than if you were on your own.
Finally, collaborating is just fun. Try it and you will see. - See #1. If you are happy with making tiny contributions to the state of the art all the time, good for you. (This is especially at odds with your apparent disgust for people who "pump out" papers, but whatever.) Meanwhile, someone will study seahorses for ten years and revolutionize the field by realizing that seahorses are aquatic poneys, rendering most of your previous research mostly useless.
- Solving things on your own is fine and valuable. Being able to use other people's ideas to solve your problem more quickly is an extremely valuable skill, however. While you will be reinventing the wheel, others will go around the world in a plane.
- This is something between you and your advisor. As a PhD student, you are supposed to transition from supervised research to autonomous research. If you really feel this way, talk about it openly with your supervisor. Maybe you will be surprised. Maybe your supervisor even thinks that you are not ready for unsupervised research because of your other points (unability to focus, to collaborate, to make use of other people's ideas and applying them to your own problem…) and this is why he is still asking you to work on something where he can directly help you and direct you in your research, instead of letting you work on something with less direction and help.
So yes, if you continue with the mindset that there are certain things about yourself that you cannot improve due to your "personality", you will have a hard time, in academia and elsewhere. You will continue to give up at the first obstacle and never amount to much. And you can continue to think that nature, your personality, your upbringing… is to the culprit, in the end, you are the one who has to live with the consequences.
New contributor
2
Just adding some nuance to your statement that "Nobody is born a good researcher.". I think it's the opposite: everyone is born a researcher. Observing babies shows that they are excellent experimental scientists: they will keep trying to do whatever it is they are interested in until they figure it out, then move on to the next interesting thing, etc. It's too bad that we lose this ability at some point in late childhood and have to learn it again later on if we want to become good at doing research.
– Guillaume
7 hours ago
1
I'm on @user108161 's side on this: I guess the "natural" thing in everyday life is jumping to conclusions - that's the way selection works: most of the time, our conclusions and preconceptions either hold or are at least (computationally) cheap. Handling (understanding, modelling) counterintuitive relations usually needs some advanced training.
– jvb
2 hours ago
add a comment |
Let me preface my answer by challenging an unwritten assumption of yours: that you have a fixed "personality" which is hampering your potential as a researcher. This simply is false. Nobody is born a good researcher. It takes hard work to become one. Sure, some people have predispositions that help them. But in the end, you cannot avoid doing the work, including work on yourself.
You have discovered that you lack certain skills, or that your aptitude for them is currently insufficient. Blaming this on your personality as something that you cannot change is lazy. It is up to you to improve in these areas. If you refuse, then you are to blame, not some god-given "personality" that was forced upon you.
I will now answer point by point, but if you are honest with yourself, you already know what I am going to say.
- There is a common saying: "jack of all trades, master of none". In math, you are studying concepts that other people have been studying and refining for decades if not centuries. You are not going to master them by studying them for a few months and moving on to the next target. You are now at the bleeding edge of research, and it takes hard work to get up to speed. Your PhD is the occasion that you get to demonstrate that you are able to become a true expert at something and make improvements to the state of the art. It is unlikely that you will manage that by working on something for six months and moving on to something else afterwards.
However, getting interested in other things is not just fine, it is mandatory if you want to have a successful career after your PhD. - You seem to be confused about what applied math really is. Math that you actually apply in the real world is usually called engineering. It is a one-in-a-million occurrence for something in applied math to find a real-world application. But since you don't know in advance what will work, you have to start somewhere. Toy models are where it's at. You start with something simple. Maybe it works. Maybe you realize it's more complicated than what it appeared (the most common occurrence). Maybe it turns out to be useless. You don't know, because you are not an oracle.
- There is nothing "fake" about getting influenced by others. Here is another common saying: in academia, we are standing on the shoulders of giants. You are reading papers, aren't you? You didn't discovered all of applied math by yourself from scratch, did you? Aren't these papers influencing your research, your way of thinking? Have you never read something and thought, "hey, I never thought about it like that", or "wow, this unrelated topic gave me ideas for my current research"? The difference with face to face conversations is that it's happening in real time. That's basically it.
And here's another saying, as I like them: alone you go faster, together you go farther. Other people have a different way of thinking, a different skillset, a different knowledge of the literature, different ideas. By pooling your resources together, you will probably be able to solve bigger problems than if you were on your own.
Finally, collaborating is just fun. Try it and you will see. - See #1. If you are happy with making tiny contributions to the state of the art all the time, good for you. (This is especially at odds with your apparent disgust for people who "pump out" papers, but whatever.) Meanwhile, someone will study seahorses for ten years and revolutionize the field by realizing that seahorses are aquatic poneys, rendering most of your previous research mostly useless.
- Solving things on your own is fine and valuable. Being able to use other people's ideas to solve your problem more quickly is an extremely valuable skill, however. While you will be reinventing the wheel, others will go around the world in a plane.
- This is something between you and your advisor. As a PhD student, you are supposed to transition from supervised research to autonomous research. If you really feel this way, talk about it openly with your supervisor. Maybe you will be surprised. Maybe your supervisor even thinks that you are not ready for unsupervised research because of your other points (unability to focus, to collaborate, to make use of other people's ideas and applying them to your own problem…) and this is why he is still asking you to work on something where he can directly help you and direct you in your research, instead of letting you work on something with less direction and help.
So yes, if you continue with the mindset that there are certain things about yourself that you cannot improve due to your "personality", you will have a hard time, in academia and elsewhere. You will continue to give up at the first obstacle and never amount to much. And you can continue to think that nature, your personality, your upbringing… is to the culprit, in the end, you are the one who has to live with the consequences.
New contributor
2
Just adding some nuance to your statement that "Nobody is born a good researcher.". I think it's the opposite: everyone is born a researcher. Observing babies shows that they are excellent experimental scientists: they will keep trying to do whatever it is they are interested in until they figure it out, then move on to the next interesting thing, etc. It's too bad that we lose this ability at some point in late childhood and have to learn it again later on if we want to become good at doing research.
– Guillaume
7 hours ago
1
I'm on @user108161 's side on this: I guess the "natural" thing in everyday life is jumping to conclusions - that's the way selection works: most of the time, our conclusions and preconceptions either hold or are at least (computationally) cheap. Handling (understanding, modelling) counterintuitive relations usually needs some advanced training.
– jvb
2 hours ago
add a comment |
Let me preface my answer by challenging an unwritten assumption of yours: that you have a fixed "personality" which is hampering your potential as a researcher. This simply is false. Nobody is born a good researcher. It takes hard work to become one. Sure, some people have predispositions that help them. But in the end, you cannot avoid doing the work, including work on yourself.
You have discovered that you lack certain skills, or that your aptitude for them is currently insufficient. Blaming this on your personality as something that you cannot change is lazy. It is up to you to improve in these areas. If you refuse, then you are to blame, not some god-given "personality" that was forced upon you.
I will now answer point by point, but if you are honest with yourself, you already know what I am going to say.
- There is a common saying: "jack of all trades, master of none". In math, you are studying concepts that other people have been studying and refining for decades if not centuries. You are not going to master them by studying them for a few months and moving on to the next target. You are now at the bleeding edge of research, and it takes hard work to get up to speed. Your PhD is the occasion that you get to demonstrate that you are able to become a true expert at something and make improvements to the state of the art. It is unlikely that you will manage that by working on something for six months and moving on to something else afterwards.
However, getting interested in other things is not just fine, it is mandatory if you want to have a successful career after your PhD. - You seem to be confused about what applied math really is. Math that you actually apply in the real world is usually called engineering. It is a one-in-a-million occurrence for something in applied math to find a real-world application. But since you don't know in advance what will work, you have to start somewhere. Toy models are where it's at. You start with something simple. Maybe it works. Maybe you realize it's more complicated than what it appeared (the most common occurrence). Maybe it turns out to be useless. You don't know, because you are not an oracle.
- There is nothing "fake" about getting influenced by others. Here is another common saying: in academia, we are standing on the shoulders of giants. You are reading papers, aren't you? You didn't discovered all of applied math by yourself from scratch, did you? Aren't these papers influencing your research, your way of thinking? Have you never read something and thought, "hey, I never thought about it like that", or "wow, this unrelated topic gave me ideas for my current research"? The difference with face to face conversations is that it's happening in real time. That's basically it.
And here's another saying, as I like them: alone you go faster, together you go farther. Other people have a different way of thinking, a different skillset, a different knowledge of the literature, different ideas. By pooling your resources together, you will probably be able to solve bigger problems than if you were on your own.
Finally, collaborating is just fun. Try it and you will see. - See #1. If you are happy with making tiny contributions to the state of the art all the time, good for you. (This is especially at odds with your apparent disgust for people who "pump out" papers, but whatever.) Meanwhile, someone will study seahorses for ten years and revolutionize the field by realizing that seahorses are aquatic poneys, rendering most of your previous research mostly useless.
- Solving things on your own is fine and valuable. Being able to use other people's ideas to solve your problem more quickly is an extremely valuable skill, however. While you will be reinventing the wheel, others will go around the world in a plane.
- This is something between you and your advisor. As a PhD student, you are supposed to transition from supervised research to autonomous research. If you really feel this way, talk about it openly with your supervisor. Maybe you will be surprised. Maybe your supervisor even thinks that you are not ready for unsupervised research because of your other points (unability to focus, to collaborate, to make use of other people's ideas and applying them to your own problem…) and this is why he is still asking you to work on something where he can directly help you and direct you in your research, instead of letting you work on something with less direction and help.
So yes, if you continue with the mindset that there are certain things about yourself that you cannot improve due to your "personality", you will have a hard time, in academia and elsewhere. You will continue to give up at the first obstacle and never amount to much. And you can continue to think that nature, your personality, your upbringing… is to the culprit, in the end, you are the one who has to live with the consequences.
New contributor
Let me preface my answer by challenging an unwritten assumption of yours: that you have a fixed "personality" which is hampering your potential as a researcher. This simply is false. Nobody is born a good researcher. It takes hard work to become one. Sure, some people have predispositions that help them. But in the end, you cannot avoid doing the work, including work on yourself.
You have discovered that you lack certain skills, or that your aptitude for them is currently insufficient. Blaming this on your personality as something that you cannot change is lazy. It is up to you to improve in these areas. If you refuse, then you are to blame, not some god-given "personality" that was forced upon you.
I will now answer point by point, but if you are honest with yourself, you already know what I am going to say.
- There is a common saying: "jack of all trades, master of none". In math, you are studying concepts that other people have been studying and refining for decades if not centuries. You are not going to master them by studying them for a few months and moving on to the next target. You are now at the bleeding edge of research, and it takes hard work to get up to speed. Your PhD is the occasion that you get to demonstrate that you are able to become a true expert at something and make improvements to the state of the art. It is unlikely that you will manage that by working on something for six months and moving on to something else afterwards.
However, getting interested in other things is not just fine, it is mandatory if you want to have a successful career after your PhD. - You seem to be confused about what applied math really is. Math that you actually apply in the real world is usually called engineering. It is a one-in-a-million occurrence for something in applied math to find a real-world application. But since you don't know in advance what will work, you have to start somewhere. Toy models are where it's at. You start with something simple. Maybe it works. Maybe you realize it's more complicated than what it appeared (the most common occurrence). Maybe it turns out to be useless. You don't know, because you are not an oracle.
- There is nothing "fake" about getting influenced by others. Here is another common saying: in academia, we are standing on the shoulders of giants. You are reading papers, aren't you? You didn't discovered all of applied math by yourself from scratch, did you? Aren't these papers influencing your research, your way of thinking? Have you never read something and thought, "hey, I never thought about it like that", or "wow, this unrelated topic gave me ideas for my current research"? The difference with face to face conversations is that it's happening in real time. That's basically it.
And here's another saying, as I like them: alone you go faster, together you go farther. Other people have a different way of thinking, a different skillset, a different knowledge of the literature, different ideas. By pooling your resources together, you will probably be able to solve bigger problems than if you were on your own.
Finally, collaborating is just fun. Try it and you will see. - See #1. If you are happy with making tiny contributions to the state of the art all the time, good for you. (This is especially at odds with your apparent disgust for people who "pump out" papers, but whatever.) Meanwhile, someone will study seahorses for ten years and revolutionize the field by realizing that seahorses are aquatic poneys, rendering most of your previous research mostly useless.
- Solving things on your own is fine and valuable. Being able to use other people's ideas to solve your problem more quickly is an extremely valuable skill, however. While you will be reinventing the wheel, others will go around the world in a plane.
- This is something between you and your advisor. As a PhD student, you are supposed to transition from supervised research to autonomous research. If you really feel this way, talk about it openly with your supervisor. Maybe you will be surprised. Maybe your supervisor even thinks that you are not ready for unsupervised research because of your other points (unability to focus, to collaborate, to make use of other people's ideas and applying them to your own problem…) and this is why he is still asking you to work on something where he can directly help you and direct you in your research, instead of letting you work on something with less direction and help.
So yes, if you continue with the mindset that there are certain things about yourself that you cannot improve due to your "personality", you will have a hard time, in academia and elsewhere. You will continue to give up at the first obstacle and never amount to much. And you can continue to think that nature, your personality, your upbringing… is to the culprit, in the end, you are the one who has to live with the consequences.
New contributor
New contributor
answered 11 hours ago
user108161user108161
1112
1112
New contributor
New contributor
2
Just adding some nuance to your statement that "Nobody is born a good researcher.". I think it's the opposite: everyone is born a researcher. Observing babies shows that they are excellent experimental scientists: they will keep trying to do whatever it is they are interested in until they figure it out, then move on to the next interesting thing, etc. It's too bad that we lose this ability at some point in late childhood and have to learn it again later on if we want to become good at doing research.
– Guillaume
7 hours ago
1
I'm on @user108161 's side on this: I guess the "natural" thing in everyday life is jumping to conclusions - that's the way selection works: most of the time, our conclusions and preconceptions either hold or are at least (computationally) cheap. Handling (understanding, modelling) counterintuitive relations usually needs some advanced training.
– jvb
2 hours ago
add a comment |
2
Just adding some nuance to your statement that "Nobody is born a good researcher.". I think it's the opposite: everyone is born a researcher. Observing babies shows that they are excellent experimental scientists: they will keep trying to do whatever it is they are interested in until they figure it out, then move on to the next interesting thing, etc. It's too bad that we lose this ability at some point in late childhood and have to learn it again later on if we want to become good at doing research.
– Guillaume
7 hours ago
1
I'm on @user108161 's side on this: I guess the "natural" thing in everyday life is jumping to conclusions - that's the way selection works: most of the time, our conclusions and preconceptions either hold or are at least (computationally) cheap. Handling (understanding, modelling) counterintuitive relations usually needs some advanced training.
– jvb
2 hours ago
2
2
Just adding some nuance to your statement that "Nobody is born a good researcher.". I think it's the opposite: everyone is born a researcher. Observing babies shows that they are excellent experimental scientists: they will keep trying to do whatever it is they are interested in until they figure it out, then move on to the next interesting thing, etc. It's too bad that we lose this ability at some point in late childhood and have to learn it again later on if we want to become good at doing research.
– Guillaume
7 hours ago
Just adding some nuance to your statement that "Nobody is born a good researcher.". I think it's the opposite: everyone is born a researcher. Observing babies shows that they are excellent experimental scientists: they will keep trying to do whatever it is they are interested in until they figure it out, then move on to the next interesting thing, etc. It's too bad that we lose this ability at some point in late childhood and have to learn it again later on if we want to become good at doing research.
– Guillaume
7 hours ago
1
1
I'm on @user108161 's side on this: I guess the "natural" thing in everyday life is jumping to conclusions - that's the way selection works: most of the time, our conclusions and preconceptions either hold or are at least (computationally) cheap. Handling (understanding, modelling) counterintuitive relations usually needs some advanced training.
– jvb
2 hours ago
I'm on @user108161 's side on this: I guess the "natural" thing in everyday life is jumping to conclusions - that's the way selection works: most of the time, our conclusions and preconceptions either hold or are at least (computationally) cheap. Handling (understanding, modelling) counterintuitive relations usually needs some advanced training.
– jvb
2 hours ago
add a comment |
Short answer to complement other longer good ones here.
You do seem really to care about the seahorses of all colors, and the pipefish and the shrimp. So focus now on learning whatever you can in your current environment. Continue reading stuff that's not directly applicable. Do collaborate. Finish your PhD (toy models are sometimes good places to start). Then look for a postdoc with someone whose philosophy and style better match yours. When you run your own lab, look for students like you.
add a comment |
Short answer to complement other longer good ones here.
You do seem really to care about the seahorses of all colors, and the pipefish and the shrimp. So focus now on learning whatever you can in your current environment. Continue reading stuff that's not directly applicable. Do collaborate. Finish your PhD (toy models are sometimes good places to start). Then look for a postdoc with someone whose philosophy and style better match yours. When you run your own lab, look for students like you.
add a comment |
Short answer to complement other longer good ones here.
You do seem really to care about the seahorses of all colors, and the pipefish and the shrimp. So focus now on learning whatever you can in your current environment. Continue reading stuff that's not directly applicable. Do collaborate. Finish your PhD (toy models are sometimes good places to start). Then look for a postdoc with someone whose philosophy and style better match yours. When you run your own lab, look for students like you.
Short answer to complement other longer good ones here.
You do seem really to care about the seahorses of all colors, and the pipefish and the shrimp. So focus now on learning whatever you can in your current environment. Continue reading stuff that's not directly applicable. Do collaborate. Finish your PhD (toy models are sometimes good places to start). Then look for a postdoc with someone whose philosophy and style better match yours. When you run your own lab, look for students like you.
answered 3 hours ago
Ethan BolkerEthan Bolker
4,1121120
4,1121120
add a comment |
add a comment |
The only problem is the issue you have about networking/collaboration. There are different styles of research and approaches, not everyone "processes" things in the same way. Having a large survey level knowledge of the field is actually very important and its a skill that often some people don't have. I recommend to acquire professional level skills on something practical and useful across fields (programming, probability, numerical methods) and then you can always apply that skillset to different problems.
add a comment |
The only problem is the issue you have about networking/collaboration. There are different styles of research and approaches, not everyone "processes" things in the same way. Having a large survey level knowledge of the field is actually very important and its a skill that often some people don't have. I recommend to acquire professional level skills on something practical and useful across fields (programming, probability, numerical methods) and then you can always apply that skillset to different problems.
add a comment |
The only problem is the issue you have about networking/collaboration. There are different styles of research and approaches, not everyone "processes" things in the same way. Having a large survey level knowledge of the field is actually very important and its a skill that often some people don't have. I recommend to acquire professional level skills on something practical and useful across fields (programming, probability, numerical methods) and then you can always apply that skillset to different problems.
The only problem is the issue you have about networking/collaboration. There are different styles of research and approaches, not everyone "processes" things in the same way. Having a large survey level knowledge of the field is actually very important and its a skill that often some people don't have. I recommend to acquire professional level skills on something practical and useful across fields (programming, probability, numerical methods) and then you can always apply that skillset to different problems.
answered 8 hours ago
mathdummymathdummy
1114
1114
add a comment |
add a comment |
Squaring the Circle is Easy is a new contributor. Be nice, and check out our Code of Conduct.
Squaring the Circle is Easy is a new contributor. Be nice, and check out our Code of Conduct.
Squaring the Circle is Easy is a new contributor. Be nice, and check out our Code of Conduct.
Squaring the Circle is Easy is a new contributor. Be nice, and check out our Code of Conduct.
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19
"I get physically sick from reading about other people's approach." This is a pretty striking thing to say and suggests something deeper is going on. You come across as rather hostile to people in general, which is going to make things tricky in any career.
– Noah Snyder
9 hours ago
some of that seems like general workplace/professionalism issues. Have your work been hurt yet? What do you want to achieve in life?
– aaaaaa
8 hours ago
11
Honestly? It sounds like you prefer "problem-solving" to research and would probably be happier in industry than academia.
– Elizabeth Henning
6 hours ago
2
"1. ... It seems to me that people who wind up obtaining a PhD learn to abandon so-called academic freedom early on and drill into a tiny research area." I can't speak for what type of maths you're doing, but I do pure maths (discrete probability), and this is not what happens. Sure, I specialise in a particular field, but it's not like I just do one thing the whole time. My supervisor has worked on stuff to do with Brownian motion, BitTorrent algorithms, percolation, random walks, random graphs -- and I would say her research is quite narrow compared with some!
– Sam T
3 hours ago
Maybe you actually have got a personality which is averse to some parts of how research is practiced at certain institutions ;) but if you pay attention to stay diplomatic, that does absolutely not mean you are doomed to fail. (Please remember, there is a large social component in doing a PhD, no matter what the technical regulations say.)
– jvb
2 hours ago