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Cool, Science-y Masters Programs For Software Devs?
An anonymous reader writes "I'm an early-30s software engineer with 10 years of development experience, and a BA in computer science from a top university. I've been working for several years at a national lab in bioinformatics, but I'm starting to wonder what other interesting directions there are to go for people in my boat: computer science majors with software development experience. The goal would be to find a position that could leverage my development skills, but also include a strong research component, without the need for a Ph.D. (I would be happy to get a masters for the right job.) I'm actually getting some of those things in my current job, but I'm ready to move on to new or different areas of research. Possible fields that seem interesting so far: neuroscience, economics/sociology, and AI. I'm happy to work in a team in support of Ph.D.s, but would like an active part in the research end of things as well as the tool-making end."
Have you considered just going for a standard master's degree in chemistry, biology, etc.? You'll probably have to take 4-6 remedial courses, but that wouldn't be the end of the world unless you absolutely can't invest the time/money.
If you really want to do a program that has one foot in Computer Science, maybe something like Brown's computational molecular biology program? It's PhD-oriented, but I'm sure they'd take your money in exchange for a master's degree.
Just graduated after 9 years as a software dev. It's a cinch as a Dev, it is interesting, and tremendously useful.
You are better off getting a Master's in the field of your choice from a top-ranked university. It is not so much what they teach you, it is the following:
1. You get exposed to a wide range of fields so you can pick and choose what really fascinates you.
2. You meet a lot of great people and network, so you can open more doors that just mailing resumes.
3. Finally, going back to school gives you the time and bandwidth to think through these issues (rather than the daily rigmarole of a job)
Good luck
Bioinformatics is currently a very interesting subject. You can dabble into cloud computing, non-relational databases, etc. And that's only from the IT side.
I'll cast my vote for computational physics. As a physics grad student myself, I find myself writing and reviewing code for simulations. And you don't need a phd to do this.
If you get any sort of training in computational physics you could be invaluable. Computational physicists are in demand in almost all fields: nuclear, atomic (simulating system-bath interactions), high energy, biophysics (protein folding sims), astrophysics, etc.
In my department, we have collaborated with the cs department in writing software for some of our sims.
How is your math background? You could get a masters in applied math and then go on to do all sorts of things -- from working in any number of fields to doing further graduate work on things like fluid dynamics or solid state physics. I also like the computational physics suggestion (being a physics grad myself), but it might be hard to get into an interesting program right away depending on your background. Good luck!
In the past few years, I've become very interested in neuroscience and I've read and studied a great deal about it. Unfortunately, the local universities don't have a neuroscience specialty, so a PhD is out of the question unless I relocate.
Computer science and neuroscience really go hand-in-hand these days. There's a great deal of research being done from the modeling of just ion channels to the modeling of entire cells, to the modeling of large-scale brain structures.
My personal belief is that software, based on neuroscience principles, will become an important area of software development for writing intelligent systems. Systems that can effectively recognize voices, faces, or interpret language, etc, are natural targets. Imagine a stock picking system that reads news stories and factors in emotional content into its picks (after all, let's face it, since the internet made stock-trading more accessible, emotion plays much heavier into the market). Systems could be designed that could monitor financial transactions to find and identify novel types of fraud. In astronomy, because of the number and quality of images coming in, one could create systems that could intelligently view the volumes of images and identify and catalog new objects.
Really, it's an area that's wide open to possibilities. But to understand how to properly piece together the types of artificial neural circuits to accomplish this kind of functionality, one would need a fairly good understanding of how the various circuits in a human brain connect and interact and how they are used to process information (we already understand a tremendous amount about this and we're learning more all the time). Really, neuroscience seems to me to be the new computer science. It's where some of the most amazing advances are being made in science today, in my opinion.
But it is just my opinion and there are lots of other possibilities. I'm definitely enthusiastic about this..
If you want to get away from the micro-scale side of biology but still use some of your skills and experience, you might consider getting into medical informatics. There's an enormous amount of R&D to be done in the areas of electronic medical records, automated order entry, clinical surveillance, drug interaction databases, etc. If you're interested in sociology and economics, data mining to determine the costs and benefits of health care is a big deal right now, for obvious reasons. If you want to go the AI route, then semi-automated diagnosis and "personalized medicine" are also very promising fields. And there's no shortage of degree programs if you want to get a Master's; a quick Google search on "medical informatics MS" turns up tons of results.
The correlation between ignorance of statistics and using "correlation is not causation" as an argument is close to 1.
Get a MS in bioinformatics and instead of concentrating on the computer science which you'll find easy at the moment, learn all the relevant biology. And then go back to the national lab.
Or, try physical oceanography/geophysics/atmospheric physics; there is substantial data analysis & software.
But, think about your career path after your degree program.
The problem is that you start to do all the real research after the masters, and everybody else is a PhD student/postdoc. And unless you want to get paid like a PhD student (unlikely since you're at a national lab and making much more $) it would be very hard for a research group to afford you. If they do have the money for a professional programmer (very few do these days) they'll want you to do the programming stuff that the grad students don't want to do (or don't have time/expertise). Even if you can program better than the grad students, you won't be appreciated in an individual research group because the essential purpose is scientific creation and the valued artifact is publishable scientific results, not an enduring software system.
You wouldn't be valued for your scientific skills much unless you are on the science track which is PhD, and if you want to do science for real that's what you need.
If you can get the job you could try to be a scientific programmer for the very large climate model codes on supercomputers which present substantial software problems beyond what a typical grad student or postdoc can accomplish on their own; that's a reasonable, though difficult career path. That's an application where the software itself is considered valuable enough to be worth maintaining professionally. Problem with this is that it is 100% dependent on Federal funding, and as it looks like Republicans are going to win the next elections and likely eviscerate climate research it may not be a large opportunity.
Are you doing this for your own personal enjoyment or do you want to make scientific contributions (i.e. publish papers in journals and contribute to core ideas). If it's the 2nd there isn't any substitute for PhD.
With the flood of PhDs in the market, nobody is going to want you to do any actual research without a PhD. With a Master's you can be a glorified lab tech, database manager, programmer, whatever, but even if you're way more than qualified, they won't let you do any significant research without a PhD.
Your best bet is to join a PhD program, deal with the significant decrease in income for five years, then get into the career you want. The more you wait and older you get, the harder it will be to take such action.
With relatively few exceptions, nobody much cares specifically where you went to school, as long as it's not Nocturnal Aviation and Degree Mill, LLC. What they care about is that you did "something" and that you did "well". You're much better off being at the top of the class at a 2nd tier school than struggling against the stars at a 1st rank school. This is both from a philosophical standpoint (it should be fun) and from a ROI standpoint (salary is correlated more strongly with class position than with school. 50th percentile starting pay doesn't vary all that much between schools)
If you're self-funding the process, then shooting for a reasonably good, but less expensive, grad school is a better thing overall. You don't have to worry about cash flow as much (which seriously distorts your thinking processes.. if you're worried about making the rent, you're not worrying about the education).
is astonishing the number of beautiful woman per square metre that you can find there, you can make some research too and well, your development skills are not needed but your dating skills will go to the roof.
Get a M.Sc. or Ph.D. in Applied Mathematics. There are plenty of schools that offer it and you might be surprised at how easy it is to be admitted to a program. Some even have an online masters program that makes it rather convenient to complete, like UW Seattle, where I got my M.Sc.
I work at a research lab connected to a large research university and having the M.Sc. definitely helps in getting to work on more interesting projects. The advantage with not having the Ph.D. is there is less burden on you to go find funding. The trick is to become indispensable to a couple of primary investigators that do completely different things to help improve job security. Where I work it is possible for a person with a M.Sc. to become a PI, so eventually if I start coming up with my own ideas, I should be able to work something out and be in charge of my own projects.
887321 = 337*2633
Pick some university department that you think aligns with your interests. Get a job as a Research Assistant or Associate. Take as many courses you want in whatever you want, without regard for whether they make a degree, while you're supporting and being part of a strong research program. If your selected courses look like some existing degree, go talk with the department head to negotiate what would be needed to convert your work into a degree. If not, negotiate an "interdisciplinary" degree with the dean's office or just live comfortably with the course credits but no degree.
You'll make less money than in industry, but that'll be offset to some extent by free tuition. Meanwhile, you'll have unlimited opportunity to explore while you "work in a team in support of Ph.D.s" and have plenty of opportunity to play "an active part in the research end of things as well as the tool-making end."
In alot of scientific disciplines Master's degree's are consolation prizes for people who get part way through the PhD and realize they're in the wrong field. (eg a master's in biology basically qualifies you for a pay raise as a lab tech but not much else) You want to pick a discipline where master's degree in itself is a useful credential. Most fields of engineering, Master of Public Health, Medical informatics are examples. If you're willing to get a PhD there are a million fields where your skills will be rare and valuable (most chemist's neuroscientist;s etc are not coders but would build themselves better tools if they were, fish biology, oceonography you name it just about. )
Look really hard at biostatistics. Pretty much all clinical medical research needs a biostatistician to be published but the Ph.D's don't get promoted checking the work of the clinical researchers and consulting for them. As a master's level statistician you could likely find work in a statistics "core" and get to help lots of different groups analyze their data at a given institution. It stay's pretty interesting because you don't get bogged down working for one group on the same project forever.
Good luck!
As a Ph.D. student in statistics with a masters in CS (mainly machine learning and AI), here's my few words of advice:
First, some masters programs are aimed at research masters, and encourage you to incorporate a strong research component to your degree, and some are more "predictable" and classroom based with smaller, more defined projects. The master's program I did at UBC - - University of British Columbia -- was heavy on the research; we took 1 year of classes and then 1 year of research. They also have a strong machine learning and AI program, which I thought was very neat. If you pursue that direction, contact me directly and I'll give you the inside scoop. Other programs may have similar research tracks, but many don't.
Second, it would really be the particular professors you end up working with that will shape your experience and how much you develop your software skills. You can learn about what a particular research group or working group is like from the websites of the professors involved and what sorts of paper and software they've published recently. I would highly encourage you to contact such professors before you apply to the university; the university admissions process is more about keeping bad people out than making sure the absolute best get in, so there's a lot of randomness in the admissions. Having a professor say "I'd like to work with this person, he'd be a big help to my research, can you let him in" usually means you get in unless the department doesn't think you could succeed. And, frankly, any professor would love to have a great coder on their team; many people without job experience can be bad coders.
Finally, if you are math inclined, and want something that could vastly help you in the job market, I'd consider doing a statistics degree. Statistics is pretty ubiquitous -- machine learning, AI, etc. are really just sexy names for statistics (yes, there's some more algorithms thrown in the mix, but the underlying theory is all statistics), and it also comes up in pretty much every other field as well. If you go to a strong research university, it's likely that you'll have opportunity to do research in a ton of different fields; I'm now at the university of washington in the stats department, and half the professors are joint with another department like economics, sociology, biology (there's a strong biostats department too), etc. I joke that it's the degree program for indecisive people, since it doesn't really limit what field you end up studying in. (Of course, not all stats programs are like this, but UW is).
Does having a witty signature really indicate normality?
Most of the people I keep track of from school are doing some kind software now. Yet none of us majored in it. We have geology, biology, physics, electrical engineering and a literature degrees among us. Its a lot easier to pick up software competency after doing science, than vice-versa.
I 'm like you, exactly 30, with a bsc in Physics. Worked in IT for 6 years then took a master's degree and now i 'm going for a phd in computational neuroscience. You won't regret it:
1) You don't need any more CS education
2) You will learn a bunch of biology stuff that is actually interesting
3) You are entering on a field that is only starting to become interesting with fundamental results yet to come
4) It is highly interdisciplinary
5) It is the new AI
6) Who knows, one day you 'll be able to see the matrix
Dude, you are not an engineer. You're a coder with some nice compsci background.
Labeling yourself an engineer may sound cool but that title is reserved for folks who completed a rigorous degree in a specific field of engineering. Not to mention those that have received their EIT and PE licenses. Those are registered with the state.
another overgrown kid wanting to know what to do when/if he grows up!
Since you're interested in Neuroscience and AI a masters in Cognitive Science is a relevant option. Every school's cogsci program is different,but they're all *very* flexible. Check out UCSD, Indiana, MIT, Carleton, Arizona, etc.
http://en.wikipedia.org/wiki/Computational_Fluid_DynamicsCFD. It's a field that is on the interface between mechanical engineering, physics and CS; applications range from aerospace, space, naval and chemical engineering to more fundamental physics, chemistry and biology - very broad.
After getting my BA in Computer Science from a top university, and feeling a bit unhappy in a software development job, I decided to go back for a master's degree in robotics.
The field is really growing, and there is a lot of fantastic research going on. In terms of hardware, robotics problems have nearly been solved -- but the software has a very long way to go.
It's great to be on the forefront of a new field, and use my CS skills to affect the real world in a tangible manner.
I know Lingustics research has turned into computer programming, haven't most of the sciences turned to computer for their theoretical research?
And trust me, WE NEED REAL PROGRAMMERS! Biologists and psychologists shouldn't be writing machine learning programs...
Is there anything better than clicking through Microsoft ads on Slashdot?
My family all seem to be engineers, computer scientists or lawyers. There really isn't that much difference whether you're checking available APIs and algorithms and using them to build software, checking technologies and codes and using them to design a building, or checking law and precedent to build an argument. They all involve abstract thought, concrete outcomes, and an ability to guess in advance how people will screw up, and try to mitigate it. Law pays more, engineering gives you greater variety of work, that's about it.
From scarped cliff or quarried stone she cries "A thousand types are gone, I care for nothing, no not one."
Use the skills you have as-is to work in health care informatics. All major insurance companies and major health care providers need people who can combine programming skills with basic statistics and data literacy to mine their data.
Perhaps you could get involved in the covert side of programming. Finding intruders or helping to find ways to secure communications may be a real up and coming field.
A problem with working in an MS level research niche like you're targeting, is you'll be trying to earn a living competing against grad students who earn ~$15K/yr. I'm not saying this makes it impossible or not worth doing, just that its something to be aware of. If you're a US citizen you have a competitive advantage for DoD research, but then there's a different price you have to pay.
Computational physics is indeed a very good choice. I'll go a step further and recommend any field where modelling is done in an operational setting, i.e. meteorology (weather, tornadoes, ...), aerosol physics (volcano ash!), oceanography, etc.
Often the difference between developing simulations just for research purposes and developing them in an operational environment is code quality. Mission critical code must be more rigorously developed, which means that there is more opportunity for CS majors to apply their software engineering skills to practice. Also funding for operational work tends to be more stable than research grants, since there are more immediate benefits to society.
There are, however, also opportunities to do research. I have a MSc in computational physics and in the few years I've worked with operational model development I've continuously had opportunities to participate in research papers. The PhD's I've worked with always seem appreciate my contributions, I have plenty of work to keep me busy and I learn exciting new stuff about nature every day.
I have a BA in mathemetics... but that is from a little liberal arts school not a "top university."
Not to be confrontational, but what's up with that?
Sell out and do a MSc in Mathematical and Computational Finance (maybe some research if you go to the right place - you could continue on to a PhD if you want) or "shudder" Financial Engineering (probably no research)!
While we're at it, I'll put a plug for my program. The University of Washington has a professional masters program (that is, the purpose is to put people in industry, not academia) in computational linguistics, though if you like the research you can stay for a Ph.D. If you're not willing to locate to Seattle, they offer parts of the degree (if not the whole thing) online (i.e. slides/audio broadcast in real time, so you can ask questions as if you were sitting in the class).
In the UK (sorry, not sure about any other countries) there are a lot of universities developing Master of Research or MRes degrees which are sort of halfway between an MSc/Ma and a Phd. I think they are 1 year but focus on research training and are more structured than phd but your thesis will still be a small research project.
Another possibility is to do an MPhil (Master or Philosophy) which is essentially half a phd. It doesn't have the constraint of making a unique contribution to human knowledge that a phd does but is still effectively a piece of research. They typically last 2 years here. Again I don't know what the position is in other countries.
I would have to recommend though that you could just work as a programmer in a group of scientists. I'm currently doing a phd but at the start of my degree I had trouble finding funding and so worked part time as a technician/sys admin/programmer/software engineer in a computational biology research group in my university. I ended up setting up servers, sorting out lab automation equipment, running a beowulf cluster, sorting out desktop PCs, debugging people's code (don't let biologists near prolog and don't attempt to write lab automation systems in excel), writing some software from scratch and being involved in the design process for some pretty complex stuff. Along the way I learnt a lot about how science in general works and also realised that some computer scientists can't actually use a computer or write code (but can devise some really complex algorithms) and that really need somebody with technical knowledge to help them.
Lots of these around the country - they have been in existence for about 10 years now, as a professional degree, like the MBA or the MD, except in science. You can look these up at http://www.sciencemasters.com/ or http://www.npsma.org/. I'm the faculty director for Georgia Tech's Professional MS Bioinformatics program, and we've had a number of CS and IT professionals come to our program and focus on biology and bioinformatics, do research with our faculty, and either go on to jobs with university and government genomics research labs or to the pharmaceutical industry. There's a real need for people who can code, develop user interfaces, and talk to biologists on their terms and understand the research needs.
Jung Choi
My advice to you is to pursue a Master's degree in Software Engineering in a school and program that is going to advance your current skill set. Find a program that has a practical approach to s/w engineering over one that emphasizes on the theoretical aspects such as teaching you a new programming language and the likes. Some course work that you might want to make sure is included included: data modeling, software testing, project management, software design and architecture. While in the program try to get yourself involved in research work just in case you ever want to move on to get a PhD at a later date. This is what I did and it has proven to be helpful in landing some amazing opportunities in various industries.
-Dickens
... as I'm in a similar situation, and doing one myself. Far from being the waste of time its detractors try to frame it as, Philosophy gives everyone a new vision into the world that I find complements nicely the more "positivist" view we technical persons are most used to.
Best Regards,
Durval Menezes.
I have never met a computer that didn't like me.
Human genetics. Rapidly expanding field, massive and noisy data sets. Jobs in both industry and academia.
--- "Many of the truths we cling to depend greatly on our own point of view." ~ Ben Kenobi, 'Return of the Jedi'
have you considered TP (Technology policy)??? it's got a good sociology and economics component and your technical background would be a big advantage...
http://en.wikipedia.org/wiki/Technology_policy
You could try something that gets you outdoor more, like civil or electrical engineering. Stay away from MechEng, as they usually end up in factory maintainance roles or as CAD people. With Electrical, you could move into one of the environmental areas, like solar / wind / alterantive energy, where your computer/software skills are very useful.
Notre Dame has a new 1-year masters program called ESTEEM combining science, entrepreneurship, and technology. I've had a couple of friends go through it with various science and engineering backgrounds and really enjoy it, though I can't give you much more advice than that. The website is esteem.nd.edu .
Do a google search for the subject of my post - it's the application of CS to Science and Engineering, without being specific to the particular sci/eng field.
BlackNova Traders
If you work in a research environment your standing lacking a PhD will be about the same as a janitor despite your expertise in software.Why not just go for the degree?
That is only true if you limit research environment to academia to the exclusion of private and government R&D programs. Once you include those, then that statement is pretty much bullcrap.
A "Discrete Mathematics and Theoretical Computer Science" program:
http://dimacs.rutgers.edu/
Spanning subjects like "mathematical logic", "automata theory", "type theory" and "number theory", a program at their institute would definitely be science-y.
In particular, if you like the idea of proving without a doubt that your program does what is intended, then this might be something for you.
For my money this is one of the most exciting "terminal Masters" degrees out there right now (of course, I'm a linguist, so probably biased).
It will serve you in bioinformatics should you choose to continue in that field subsequently, will definitely tax/challenge your coding chops, and will teach you some cool stuff about language. Also, some of the people who run this program are affiliated with MS Research (you know, the cool arm of MS), and doing this degree is plausibly some kind of foot in the door there.
Research is what I'm doing when I don't know what I'm doing. -- Wernher von Braun
I got a masters of science in math last year from Texas A&M. It was a fun program, quite educational, and decently affordable for an in state resident. They've got a distance option if you want to keep getting paid.
John
a top university offers a BA in CS?
(Sorry if this sounds a little bit gruff.)
$META_SIG_JOKE
Most of the people I keep track of from school are doing some kind software now. Yet none of us majored in it. We have geology, biology, physics, electrical engineering and a literature degrees among us. Its a lot easier to pick up software competency after doing science, than vice-versa.
Not necessarily true. It's just that there is much more need for folks to understand software in this day and age.
As a professor and (obviously) former grad student, I have some advice about your choice of Masters vs. PhD. The above posters have made good comments about the advantages of each, but there is one more thing to consider when you are applying for graduate programs - many universities simply are not interested in taking on anyone who intends to stop at the Masters level. To be honest, most grad students don't become useful until they have been in the program for a couple of years and have learned the ropes. Plus, the first couple of years of any grad program will contain more coursework (and therefore less research time) than the latter years. In other words, a PhD student who is there 4 years is worth more than 2 MS students who are there 2 years each. Therefore in a down economy when student applications are up, anyone who announces their intention to stop at a Master's degree is automatically put into the reject pile. My advice is that if after considering your options, you still think a Master's is what you want, go ahead and state on your application that you want a PhD. In many programs, the first two years of PhD. work are almost identical to the Master's work so it will not affect your studies. Once you are admitted to the program, you can always "change your mind" and decide to stop at a Master's. Or, who knows, maybe you really will change your mind and get the Doctorate for real.
I think you will definitely want to investigate 'Statistics' as a career path to any of the above possibilities. It will open doors for you, and the pay is clearly on an upward trajectory for at least the remainder of our lifetimes. There was a big, front page article about it on the front page of the New York Times within the last year or so - check with the Science Times editor there. Everyone from Casinos, to the military, to the canyons of Wall Street to the upper echelons of every last Search Engine such as Google hire them in droves. They can be found in any high tech environment, where computers are used to analyze vast quantities of information. They are in very big demand today since the advent of the PC and Internet in the last two decades.
I'm in much the same situation as you, although I only recently got my Bachelor (and not exactly a "Top" university, but it was a good program).
I applied to and just got my acceptance into the MS in Digital Forensics program at UCF. Other than the obligatory "Topics In" course, it looks like it's going to be cool as hell (for some slashdot-appropriate value of "cool").
If you're really good, go work for Aveva.
So what is it precisely about 'science competency' that you think seems to be difficult for computer scientists to pick up? I may be personally biased because I hold degrees in computer science, but I look at the subject as the culmination [and future] of all the other sciences.
Since I began here 1.5 years ago, they started ANOTHER program called "Global 30", which means they're recruiting 300,000 foreigners for research, Master's, and PhD's from now till 2020. All over Japan. Here's an example of the program from Kyoto University. http://www.opir.kyoto-u.ac.jp/kuprofile/e/courses/index.html There are lots of programs in different fields, at different universities (Waseda, Tokyo University, Osaka University), so just browse around for what you like.
Several years ago I have completed the MSc. in Scientific Computing at Utrecht University, in the Netherlands, which is an interesting program dealing with computational aspects of programming. A fair bit of Matlab, some C, some Fortran. Feel free to consult the website for more information: http://www.math.uu.nl/people/bisseling/sc/
The science part is mostly in numerical mathematics. The algorithms can be applied to every other scientific field, ofcourse.
to re-career as a climate scientist. There was a post from someone who counts on their toes earlier. between the two of you you could maybe save a polar bear or 1023
You have to be damn good already. Yep, that's a kind of catch-22. Employers are wary to get person without PhD for research position (And would readily get PhD with couple of publications instead). However if you already have proven to be expert in the area and already have some records of successful projects they would gladly take you. So I'd recommend the area where yo can teach yourself and prove your abilities (for example with OSS project) before you actually change the job. Statistics was already recommended and its' great, and I'd also recommend it's aplications to machine learning(if you like AI). Things like evolutuionary programming (genetic programming etc) are also good area to start.
like the one i work at: http://www.mixedreality.nus.edu.sg/ there are many more like this all over acedemia, which employ practitioners from a wide range of fields to collaborate.
I think it would be tough to jump into graduate studies in pure neuroscience. I completed my B.Eng in Computer Engineering six years ago and have been doing software dev professionally since then. I am starting a master's degree in Computational Neuroscience this October at the BCCN in Berlin. This would be a more reasonable transition for someone with a background in computer science. The hard part is finding schools offering a master's program. There are plenty of PhD programs but not so many master's. It's still worth investigating though. Some schools call their programs Neuroinformatics while others prefer Theoretical Neuroscience.
Another side of a similar coin is getting an MBA. That could be very useful for somebody who has been doing anything professionally for 10 years, and is interacting with management/investors, leading teams, doing product/project direction, or becoming an entrepreneur.
I am a microfab engineer/physicist for a small (5 people) microfluidic genomics company. We have a software portion of our device that is being done by one person. I would say there are a wealth of opportunities in both implanted and external medical devices, wireless biosensors, MEMS etc for a interested dev. For example a retinal implant being worked on by colleagues has about 4 fulltime post docs and PhDs just working on pure image recognition and decoding algorhythms, whereas our guy is working on a whole suite of software for our bioseparations chip that future customers and/or I will need. You may take a pay cut but I would say the potential rewards both material and immaterial are well worth it.
/shameless-plug
Take a look at the MIMS at UC Berkeley iSchool, it's CS-y but interdisciplinary. CS, law, econ/sociology and business are all part of the core curricula, and several student final projects have been pretty cool.
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There are some great courses usually called MA New Media or MA Digital Media that leverage your skills in CS but bring in cool research from sociology, political economy, political science, anthropology, critical legal studies, etc. They usually feature research skills as part of the training and really encourage critical approaches to new technology.
Google search for courses
There are think tanks which hire researchers/computer scientists to work on various projects which might be right up your alley. The one I work at is called Southwest Research Institute, but there are others. I work primarily in space research and have a BS in Computer Science from a local university. Some of my work has even shown up on Slashdot! I freely admit I know very little about space compared to the astronomers and physicists I work with; however, I use my computational/development skills to make it easier for scientists to do science. We have other divisions as well besides space, but none of them really fit exactly what you mentioned you were interested. Nevertheless, you may want to check them out...
Ah, another CS major getting all huffy when they see non-CS majors doing their work. Hint: your degree doesn't mean you can develop software. In fact, many of you get so lost in theories of design you can't make the first step to solving the problem.
I'm impressed! Whoever approved posting this you got pwned.
-- Programming with boost is like building a house with lego. It's a cool but I wouldn't want to live in it
I was a CS undergraduate major and I also was looking for new areas of research. I recently completed a Masters of Applied Cognition and Neuroscience at the University of Texas at Dallas. I took a mixture of classes in neuroscience, computer science, and AI. The AI classes were focused on approaching the subject from the perspective of the human brain. It was very fascinating and I could have gone on for a PhD (which was my original plan) but then I discovered that I did not like the heavy research end of that subject. However, you might like it. They were doing some very interesting studies in bionics. Hope you find what you're looking for. Cheers.
I agree. I should've chosen the other side of the coin and studied Biotech instead of CS. There's also a bit more back water in CS as it's seen as a new field that there aren't qualifications necessary for. I have no regrets as I like CS but in the real world Biotech is more stable to fall back on than CS IMO. "Anyone" can work in CS..
Look at public health metrics. The University of Washington has a great new program called IHME which could certainly use some quality programmers. Their approaches include a lot of Bayesian stuff, but also some machine learning, a lot of modeling, and various other things that are pretty interesting.
As a early-30's programmer who is back for a MS in EE/CS, I've made a number of friends with grad students in fields that are quite science and computationally related. I'd recommend looking into:
Linguistics, especially Computational Linguistics ... especially Agent-Based Simulation, which can be applied, IMHO, to a lot of sciences.
Cognitive Science, especially related to AI
Computer Simulation
I'd also second the previous posts on Bioinformatics and Computational Physics.
Also, I always strongly recommend that if you can get a PhD, you should. In the US, the statistics are quite stark, only 30% of PhDs in Science, Technology, Engineering and Math are awarded to US Citizens. What's going to happen when all those Indian and Chinese PhDs start going home?
Best of luck!
I don't fear computers, I fear the lack of them. -I. Asimov
Masters in EE is probably the way to go. You can even do a focus on Biologic or Chemical related EE too - thus you'd essentially have the training as a Computer Bio or Chemical Engineer. Think along those terms, and there's probably a good fit from the Engineering perspective for you.
Truth is like the sun. You can shut it out for a time, but it ain't goin' away. - Elvis Presley (source: imdb.com)
Just go get a Master's.
Why are you asking us anyway? You're at a national lab. Throw a rock. Whoever it hits, ask them how you can get into a position where you have a more active role in research. They'll have a much better, tailored, specific answer for you.
Just a warning to the poster: Unless you've already succeeded in doing some research, you may discover that you are more valuable to academics if you spend 100% of your time building tools, and they'll have very little incentive to help you pursue your own interests.
I tried this and failed. I hope you have better luck :-)
I graduated with a CS degree in the '90s, did software development for several years, became a development manager for a large company, and *then* decided I wanted to do science with my life instead of living as another incarnation of one of the OfficeSpace characters.
Neuroscience fascinated me, but I had no neuroscience training. So I worked in an fMRI lab as an RA for a year or two while I took courses and figured out if this field would be really satisfying. At the time, I was 30 years old, so I was a good bit older than most RAs. Getting an RA job was pretty straight-forward though, as most CogNeuro labs are absolutely desperate for technically skilled research assistants.
It turns out, most of the other posters above me are absolutely correct -- if you want to be taken seriously in research, you'll want to get your PhD. Emphasizing that a little differently, after working in a pure research lab, you'll WANT to get your PhD. Not just because you'll have hip science credentials, but because once you realize you like research, you're probably going to want to do YOUR OWN research, and having a PhD is pretty much the only way to do that.
Anyway, I'm in my 5th year of my PhD now, and I continue to love it. I can't believe people pay me to do what I'd be doing for fun anyway. Leaving a big salary is scary (I took a $120,000 pay cut), but it's so worth it to figure out what you like to do in life.
So, the OP has a job but wants to quit and go back to school in hpes of getting an even better job...in the middle of a global economic recesssion.
bwah ha ha ha ha!
OP, you are a self-absorbed punk. Please, do quit your job in order to join the massive pool of talented but under/un-employed people. I know people
looking for an opening.
Also, you might want to read the news.
HTH
Engineers get so wrapped up in problem solving that their solutions look rather much like this
Woods Hole Marine Biological Laboratory has a 4 week summer seminar on Methods In Computational Neuroscience. It's too late to apply for this year, but you might try again next year.
September 2011: Looking for Cocoa/iOS work in Boston area Cocoa Programmer Quincy, MA
Anyone have an opinion on the UMass Boston CS master's/PhD programs?
September 2011: Looking for Cocoa/iOS work in Boston area Cocoa Programmer Quincy, MA
Why not computer science research? This also applies for AI. If you're looking for a terminal master's program, Colorado State has an online "Master's of Computer Science" that I'm pursuing part time (as of this fall), while working at a national lab full time (good way to get your classes paid for). Just taking 1-2 classes at a time, I should be done in 2-3 years. And since it's online, it will save me 1-2 hours of drive time every day.
If you're set on something more "science-y", I'm sure there are similar options. Colorado State has an online M.S. in Statistics too. And of course there are several other well known schools that offer online degrees - Stanford, U of Illinois, NC State, etc. Perhaps one of those would have an online program you'd be interested in.
The "online" degree is identical to the on-campus one, so no future employers will know you took it online unless you tell them.
Georgia Tech has relatively new MS and PhD programs in Computational Science and Engineering, which is specifically for people who are interested in the interface between computer science and computer-based modeling for "domain" sciences. Many of the faculty, who are jointly appointed between computing and science/engineering departments, are developing and applying techniques in high-performance parallel computing to problems in computational biology, traffic simulation, biomedical engineering, aerospace engineering, and massive-scale data analysis, to nname a few. See http://www.cse.gatech.edu
My physician gets all huffy when I treat my kids with DIY pediatrics at home. His medical certification doesn't mean he can treat people! In fact he gets so wrapped up in terminology like "distal sassafras obliquity glomerulus" that he can't even get my Chi aligned and balance my four bodily humours.
$META_SIG_JOKE