Cool, Science-y Masters Programs For Software Devs? 150
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."
Obvious answer... (Score:5, Informative)
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 [brown.edu]? It's PhD-oriented, but I'm sure they'd take your money in exchange for a master's degree.
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Or you could keep the computer science side of things as your focus and work on biologically inspired systems. Artificial Intelligence, Robotics, and Computer/Machine Vision are all good candidates.
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I think that would depend a lot on where you work and how needed your expertise is.
Someone with two degrees, one in CS/CE and another in the field at hand could probably be considered very valuable although I'm sure there are stuck up researchers who would look down on you for "only" having two degrees in different fields instead of a single PhD.
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not true (Score:2)
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.
Law School. (Score:1, Interesting)
Just graduated after 9 years as a software dev. It's a cinch as a Dev, it is interesting, and tremendously useful.
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How would you contrast what's hard about law school vs. software development?
For example, do you have to memorize far more for law school?
Re:Law School. (Score:4, Insightful)
There wasn't much memorization in law school (now studying for the bar is a different matter). I loved it because law is essentially programming. Both law & software provide a set of instructions that you are supposed to follow to get a result. In law, your processor may or may not follow the instructions, or may not even understand the instruction set that is being used, and moreover each processor's interpretation may affect (i.e. screw up) subsequent processors. In software, your processor does exactly what you told it to, whether you want it to or not. The end result of both is bugs, either leading to re-factoring, hacking, or wholesale replacement.
Leaving aside ideological positions for the moment, Roe V. Wade is a good example. The legal framework from that case was an unworkable "trimester" framework that was subsequently replaced in Planned Parenthood v. Casey with the "point of viability" test, which arguably isn't much clearer (when exactly is the point of viability?) in programming, there really can't be any uncertainty because a processor can't handle it. In law, the entire game is "where to hide the uncertainty." In tort law, uncertainty hides behind the "reasonable person." Want to know what the standard of care is? It is what a reasonable person would do. It is a fascinating study in sociology & logic.
Finally, as a programmer, it is relatively easy to understand. What a lot of your classmates and up struggling with will seem like a relatively trivial set of if-then statements compared to the nasty logic you had to sort through as a programmer. And if you are seeking to either exploit or overturn the existing IP framework, what better way than to understand it from the inside.
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Heh. In reality, software is usually more like you describe law. Computer may do "
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So law is like javascript?
Re:Law School. (Score:4, Insightful)
No offense, but I'm guessing that anybody with the same interests as the OP would find the topic of law wrist-slashingly dull.
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Re:Law School. (Score:4, Funny)
Fully automated systems are discouraged.. But what if a big law firm wantted to analyze all previous decisions on a subjuct, then apply a statistical liklihood that a given judge will decide in your favor, based on the judge's previous judicial bias? It's not much different than trying to predict the stock market, really. Though it does add a few more variables.
As we said: wrist-slashingly dull. Law is just excruciatingly boring to most people.
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Yeah, for most people it's nowhere near as interesting as sitting in a cubicle writing code. That's why there are so many TV series, thrillers and movies about computer programmers, and almost none about lawyers.
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even just a legalese to English translator would be a non-trivial problem.
It would probably also be illegal because it would put some lawyers out of business.
Legalese is not a way to state things precisely and accurately. (I once naively assumed it was). I've learned that legalese is written to sound precise and accurate while being as open to interpretation as possible. These worlds collide when trying to write a patent - no good engineer could possibly write (or read and understand) a patent. Engineers write it, then the lawyers obfuscate it so it can be as broad as possible
You'd be surprised (Score:5, Interesting)
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Just graduated after 9 years as a software dev. It's a cinch as a Dev, it is interesting, and tremendously useful.
How's the job search going? It seems lawyers are harder hit than many others in white-collar jobs by the Depression.
MBA (Score:2)
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.
Better off... (Score:1)
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 (Score:2)
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.
Computational Physics (Score:5, Interesting)
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.
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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.
Perhaps not in physics, but you ought to have a very thorough training in numerical analysis (i.e., not just one course or two). Like the OP I work at a national lab (as an applied mathematician). I find there are way too many physicists working in isolation that think "numerical recipes" is extent of what they need to know to do computational physics, and not surprisingly, poor-quality numerical (and scientific) code is often the result..
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I find there are way too many physicists working in isolation that think "numerical recipes" is extent of what they need to know to do computational physics, and not surprisingly, poor-quality numerical (and scientific) code is often the result..
I have to second this. There are some fields in which the researchers are not strongly mathematically-minded, let alone numerically-minded, and it does indeed lead to inefficient code that produces results which may be incorrect in ways they never thought to check. You could easily be a hero (or villian) if you can get into one of these research communities with good software and numerical skills: you can sometimes make their code run in O(n) or O(n log n) time instead of O(n^2) (or worse), but you may al
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Can you give an example where a complexity change improves the accuracy
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Sorry if it appears that I'm conflating the two; I didn't mean to imply that accuracy and complexity are necessarily related. I meant that sometimes one can find ways to reduce the complexity of a correct implementation without affecting accuracy, and sometimes one will find that a numerical method has been implemented incorrectly, or that the selected method isn't applicable to the problem at hand, and therefore the results produced may be wrong.
The general case I'm talking about for reducing complexity i
Re:Computational Physics (Score:5, Interesting)
Operational simulations (Score:2, Interesting)
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 ap
Applied math? (Score:3, Interesting)
Neuroscience (Score:4, Interesting)
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..
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I'm studying for my PhD in Computational Neuroscience currently. I studied for a BSc in CS from the institution previously (and a BSc in Psychology prior to that). The Computing Department I am in does not have a Neuroscience speciality... lots of work on ANN's, expert systems and other Cybernetic/AI topics... But only one individual looking at anything more than point/concept Neuron models (2 with me now). Specifically I'm looking at Compartmental models, and population responses and the role of Noise in N
Computational Neuroscience (Score:1)
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
medical informatics (Score:3, Informative)
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.
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how many of the results on a search for "medical informatics MS" are for a Masters of Science and not Multiple Sclerosis?
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Heh. On the couple of pages, at least, all of them are for the degree, not the disease. Long-term grad students might argue that there's not really much difference ...
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Argh. "On the first couple of pages ..." etc.
You're already doing it. (Score:5, Insightful)
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.
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Apologies for the self-reply, I already submitted it.
There is something else to consider: the average biologist is a much worse programmer & mathemetician than the average physical oceanographer/geophysicist, and hence biologists need (or more specifically know they need) professional software & computational scientists much more than physical scientists do.
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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.
I've got to tastefully disagree. I am a professional programmer, I am on a masters track, I get paid like a PhD, and I do the research of a PhD. A PhD is simply part 2 of my research, if I choose to do it. If there are no universities in the USA that can afford you, then come to a Canadian University (University of Waterloo, University of Toronto, University of British Columbia) . There is lots of research money up here. We have produced as much research and development as any country in the world (satell
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Re:You're already doing it. (Score:5, Interesting)
Outstanding advice. I have a BS in bio and an MS in CS plus 20 years of experience, 80% in R&D (supercomputing/sci programming, DoD C^4I, AI). Presently, I do medical image analysis R&D in a giant pharma. My experience confirms mbkennel's advice. But I would avoid scientific programming. It's a support job that leads only to more of the same. You will likely work beneath postdocs and remain employed only as long as long as your current project remains funded.
More generally, without a PhD you will never lead an R&D team. You will always be a subordinate. This is worst in pure sciences, in academia and at large east coast corporations, and probably best in engineering and at small startups.
My recommendation: look at jobs in bioinformatics (or even comp. bio) that 'require' a MS. Talk to others who are working in such a role to learn whether they really are in a leadership position (and not just extolled the potential of one).
Also: consider a MS in one of the engineerings -- EE, ME, Mat Sci, or Eng Sci. Then find work in industry. Licensed professional engineers are recognized by most for-profit employers as first string players and team leaders. The folks who lead engineering teams, no matter how large (like space shuttles or 787s), usually are pro engineers w/ MSs, and not PhDs. The exceptions are, again, east-coast giant corporations who are more afraid of failing than excited about winning.
Finally, avoid a degree in the sciences unless it's a PhD + postdoc(s). There's a perpetual glut of PhD physicists (and soon, chemists & biologists). When competing for a science job, a MS in science will lose out to these folks every time (since the project manager will also have a PhD, and will see you as 'one of *them* and not 'one of *us*').
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I am a dynamic figure, often seen scaling walls and crushing ice. I have been known to remodel train stations on my lunch breaks, making them more efficient in the area of heat retention. I translate ethnic slurs for Cuban refugees, I write award-winning operas, I manage time efficiently. Occasionally, I tread water for three days in a row.
I woo women with my sensuous and godlike trombone playing, I can pilot bicycles up severe inclines with unflagging speed, and I cook Thirty Minut
Can't do research without PhD (Score:2, Informative)
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 a
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Applied Mathematics (Score:4, Informative)
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.
Work as an RA for a while? (Score:4, Interesting)
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."
Terminal Degree and Biostat's (Score:3, Informative)
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!
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I can second this. I did a Master's in Biostatistics, and have a computing background from undergrad. It sounds like this would be a good fit for you, since you're working in a related field already. In the five years I've been working at universities since my Master's, I've had a lot of different experiences, ranging from large clinical trials to military projects. Your computing background will make you a very valuable asset to almost any group you work in, as a lot of stats people are entering from a
It depends (Score:5, Interesting)
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).
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I'd only add that just because a professor says he wants you doesn't necessarily mean that helps your chances of admission at all. If they aren't on the admissions committee, then their wishes might mean squat, no matter what. Departmental politics plays a bigger role than anyone would like, and can rear its ugly
my MIT classmates do software; none majored in it (Score:4, Informative)
Re: my MIT classmates do software; none majored in (Score:5, Insightful)
(Sorry if this sounds a little bit gruff.)
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Jeezus! (Score:3, Funny)
another overgrown kid wanting to know what to do when/if he grows up!
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Cognitive Science (Score:2, Informative)
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.
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As a cognitive science grad student I couldn't agree more. In the field computationalists are modeling everything from single neurons to whole brain recordings, as well as larger systems such as insect colonies, networks of people for software collaborations, composition of music, really anything you could imagine discretizing. In particular at UCSD there is a pretty healthy Human-Computer Interaction laboratory group that focuses a lot on the design/development side which you seem to be interested in. I
Most of the sciences need programmers, badly (Score:2)
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...
Homeland Security (Score:2)
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.
Two observations (Score:2)
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.
Get a Masters in SW Engineering (Score:1)
I recommend a bacharelate in Philosophy... (Score:1)
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As someone who majored in CS and minored in Philosophy, I can tell you this is a horrible idea. Philosophy, like CS or (to to some degree) math, can be learned though self-teaching in your spare time.
I disagree that philosophy can really be learned on someone's spare time: without a good teacher, most of the serious and important works (take Kant's Critique of Pure Reason as an example) are almost impenetrable. Unless you have a real knack for it, the most you will be able to read (and really understand) would be introductory texts and the like.
Also, employers actually see it as a deterrent, to the point that I quit listing my minor on my resume.
I was under the impression that the Original Poster was, like me, looking more towards personal satisfaction and intellectual enrichment than to complement his C
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I'm quite a big fan of philosophy, but if you're looking for a degree to help your career (as the submitter is), then stay far, far away from the philosophy department.
I agree to that it can be detrimental in atechnical curriculum, given the widespread (and, in my opinion, wrong) view that philosophy is useless or that it has no relation to CS or business (see below). On the other hand, I was under the impression that the Original Poster was, like me, looking more towards personal satisfaction than to complement his CV towards current/future employers... in the former case, I maintain that philosophy is still a good course.
The fact of the matter is that, while it's interesting, it doesn't teach any skills that a business finds worthwhile.
This is indeed the prevalent view, but (in my h
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Don't forget, ethics is an integral part of philosophy. And corporations do NOT like ethics.
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You've obviously never worked at a large company.
Well, in fact I've worked for a few of them, back in the times before I started my own company.
While those things may be valuable to a small business, but unless you're one of the executives at a large business, a large business doesn't care about your views (so rhetoric is out) and they definitely do not like logic, because then you'll realize what utter morons the people in management are.
I agree that this is the way it works on most large corporations (heck, in small corporations too), but please notice above my observation about the OP doing it for himself and NOT to "pump up" his CV...
Human Genetics (Score:2)
Human genetics. Rapidly expanding field, massive and noisy data sets. Jobs in both industry and academia.
Why not one of the engineering disciplines (Score:1)
ESTEEM (Score:1)
Computational Engineering and Science (Score:2)
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.
Comp Ling (Score:2)
For my money this [washington.edu] 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 th
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--Greg
Masters Vs PhS (Score:2, Informative)
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
STATISTICS !! (Score:1)
Same here (Score:2)
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").
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Sorry for the self-reply, but I meant to mention that this is a "professional" Master's track, intended to be put into use professionally as opposed to academically.
CAD (Score:2)
Come do a Master's in Japan (Score:1)
Since I began here 1.5 years ago, they start
To get research positioin without PhD (Score:2)
you could try a multidiciplinary lab (Score:1)
Southwest Research (or other research orgs) (Score:1)
great way to get your resume posted free! (Score:2)
I just did this (Score:2)
Public Health (Score:1)
Look at public health metrics. The University of Washington has a great new program called IHME [healthmetr...uation.org] 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.
A couple other options (Score:1)
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 tha
EE... (Score:2)
like everyone else said, just go do it (Score:2)
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.
From someone who did this... (Score:1)
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 go
Woods Hole (Score:2)
Woods Hole Marine Biological Laboratory has a 4 week summer seminar on Methods In Computational Neuroscience [mbl.edu]. It's too late to apply for this year, but you might try again next year.
BTW, how's UMass Boston's program? (Score:2)
Anyone have an opinion on the UMass Boston CS master's/PhD programs?