It sounds like you’re doing some awesome work, and these are great questions, but I very seriously doubt you will be able to get good answers to them from anyone without domain expertise in your field, so this may not be best place to look. I personally have some very cursory exposure to biostatistics and health data science (definitely less than you), but I imagine I have significantly more familiarity with the area, especially in the U.S., than most people on the EA Forum, and I have zero clue about the answers to your questions.
Maybe so! Might just be the career questions are a bit too targeted (partner also has had trouble getting advice on how to best leverage her tissue engineering / veterinary background to best serve animal welfare, e.g. working directly with researchers using animal models vs. developing in vitro meat in a more wet bench role). Was just curious to get an outside view, especially from a more “value-aligned” group than might be found in your typical career center or through existing mentors etc. Thank you for your response!
My experience with bioinformatics is almost exclusively on the industry side, and more the informatics than the bio. With that caveat, a few thoughts:
should I prioritize developing skills that will make me more employable and E2G (e.g. develop and apply sexy, ad hoc methods to rich-person illnesses in a more mainstream bioinformatics-y role)
My experience is that the highest earning positions are not “sexy” (in the way I think you are using the term). I recall one conference I attended in which the speaker was describing some advanced predictive algorithm, and a doctor in the back raised their hand and said “this is all nice but I can’t even generate a list of my diabetic patients so could you start with that please?”
This might also address your question “how easy is it to, say, break into industry data science for anthropology graduates with experience in computational stats methods development?” – I think it depends very much on what you mean by “data science”. A lot of the most successful bioinformatics companies’ products are quite mundane by academic standards: alerting clinicians to well-known drug-drug interactions, identifying patients based on well validated reference ranges for lab tests, etc. My impression is that getting a position at one of these places is approximately similar to getting any other programming job. If you are looking for something more academic though, the requirements are different.
focus more on greater blights afflicting larger numbers of human and non-human animals (say, to understand differential responses to tropical diseases, or maybe variation in the human aging process, or pivot to food science and work on cultured meat or something, as well as work on more interpretable methods)
A problem I suspect you will run into is that methods development requires (often quite large) data sets. I get the sense from your brief bio that you aren’t interested in doing any wet lab work, meaning that if you were to work on, say, cultured meat, you would need a data set from some collaborator.
If I were you, I might try to resolve this first. I know GFI has an academic network you can join and you could message people there about the existence of data sets.
Also, you might be interested in OpenPhil’s early career GCBR funding. Even if you don’t need funding, they might be able to connect you with useful collaborators.
(removed for privacy + inappropriateness)
It sounds like you’re doing some awesome work, and these are great questions, but I very seriously doubt you will be able to get good answers to them from anyone without domain expertise in your field, so this may not be best place to look. I personally have some very cursory exposure to biostatistics and health data science (definitely less than you), but I imagine I have significantly more familiarity with the area, especially in the U.S., than most people on the EA Forum, and I have zero clue about the answers to your questions.
Maybe so! Might just be the career questions are a bit too targeted (partner also has had trouble getting advice on how to best leverage her tissue engineering / veterinary background to best serve animal welfare, e.g. working directly with researchers using animal models vs. developing in vitro meat in a more wet bench role). Was just curious to get an outside view, especially from a more “value-aligned” group than might be found in your typical career center or through existing mentors etc. Thank you for your response!
My experience with bioinformatics is almost exclusively on the industry side, and more the informatics than the bio. With that caveat, a few thoughts:
My experience is that the highest earning positions are not “sexy” (in the way I think you are using the term). I recall one conference I attended in which the speaker was describing some advanced predictive algorithm, and a doctor in the back raised their hand and said “this is all nice but I can’t even generate a list of my diabetic patients so could you start with that please?”
This might also address your question “how easy is it to, say, break into industry data science for anthropology graduates with experience in computational stats methods development?” – I think it depends very much on what you mean by “data science”. A lot of the most successful bioinformatics companies’ products are quite mundane by academic standards: alerting clinicians to well-known drug-drug interactions, identifying patients based on well validated reference ranges for lab tests, etc. My impression is that getting a position at one of these places is approximately similar to getting any other programming job. If you are looking for something more academic though, the requirements are different.
A problem I suspect you will run into is that methods development requires (often quite large) data sets. I get the sense from your brief bio that you aren’t interested in doing any wet lab work, meaning that if you were to work on, say, cultured meat, you would need a data set from some collaborator.
If I were you, I might try to resolve this first. I know GFI has an academic network you can join and you could message people there about the existence of data sets.
Also, you might be interested in OpenPhil’s early career GCBR funding. Even if you don’t need funding, they might be able to connect you with useful collaborators.