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Ask Slashdot: Which Ph.D For Work In Applied Statistics / C.S.?
New submitter soramimo writes "I'm currently a Ph.D student in Machine Learning and Biology at a pretty good European university. As my lab is moving to the U.S., I have the chance to get my Ph.D from an Ivy League university instead of the one in Europe (without much additional work, as I'm close to finishing). However, I would be getting a Ph.D in Biological Sciences rather than Computer Science. As I'm planning to work as an applied statistician / computer-scientist / analyst in the U.S. after graduating, I'm wondering which path to take. Is a Ph.D in Biological Sciences frowned upon by technology companies, or is it out-weighed by the Ivy League tag? How big of a role does the type of Ph.D play in the hiring process in the U.S., compared to what you actually did (thesis focus, publication record, software)?"
Employers will care about what you did more than what your degree is named. There are lots people working in fields that don't correspond to the subject-name of their PhD degree.
If it weren't for deadlines, nothing would be late.
You're hiring a someone to be a computer scientist. Would you rather see them have a CS degree or a biology degree? Ivy League degree or Pretty Good European University? I think everyone is going to look at this differently. I know *I'd* rather see the CS degree. I wouldn't be overly impressed by Ivy League but I think a lot of others would be. I work in the the tech field along with people who have degrees in unusual areas (Dance?) but are technically top notch.
BTW, these days it seems a lot of resumes are searched for key words. If they're hiring a computer scientist - guess what keywords they're going to look for?
Bio-informatics is a good place to be an applied statistician. There are also good opportunities in neuroscience, especially if you want (or are willing to) do experiments. Some of the data analysis and acquisition code is pretty sophisticated, and a grad student from my last lab got a good CS job by doing that. Further, any lab that uses super-resolution or EM microscopy is a good place to look. If you tell me which school, I can perhaps give you a few names.
He once inserted random mutations into his code, just so he could have the experience of debugging.
In my experience, the employers that really want Ph.Ds are educational and research institutions, and the odd technology company that wants to have some additional buzzwords to put on slides. It doesn't really add much for a technology company, unless your area of study is very specific to their business area. I'm kinda scared of any place that would do hiring based upon a degree or where it came from rather than what the person can actually do.
In my experience when the lab moves the students either (1) get a degree from old university or (2) apply to new university and go through the qualification process over. I would check again, before assuming it is your decision. I even know a case, where a 3rd year grad student at Yale was turned down acceptance into Berkeley grad school
From my experience in semiconductor manufacturing, technology companies frequently hire individuals with degrees and areas of research that deviate from the core function of the business. Be prepared to discuss the details of your research and work while pursuing your degree and you will do fine.
Many of the skills utilized in your education are common across job fields and in some cases they are not utilized as often as they should in the work place. Some examples include...
- The scientific process itself. A sound decision process is key to problem solving within technology businesses and all too often mistakes are made by "gut feeling" or "common sense" decisions that are followed far too quickly without proper critical thinking.
- Understanding statistical significance and proper reading or presentation of statistical data. This is a hugely critical field to technology companies and at the same time a massive weak point in U.S. businesses. In my opinion there should be some basic statistics courses in K-12 education.
- Working in groups. U.S. corporations spend millions in consultant and training fees trying to instil some group working skills into employees but from what I have seen it is very difficult, and in some cases impossible, to teach people to set aside their individualistic wild west cowboy mentality.
- Communication and presentation skills. Meetings are frowned upon, partly due to the lack of group work skills, yet they are also necessary. You will quickly lose an audience that already doesn't want to be there so you need good communication skills to both keep the attention of individuals but also to transfer the information and knowledge effectively.
There are many more, of course, but these are just a few that come to mind.
As someone who worked in High Finance, I can tell you that you are full of it. Most of the employees were science and liberal arts Ph.D's with very few of those degrees directly relating to what they were working on. My manager (I was doing fixed-income pricers) was a Chemical Engineering doctor, my partner on the project had a Ph.D. in english. There are other examples, but I'll stop there. All that matters is aptitude.
Biological Science. Any scientist these days is going to have to be proficient with computers and analyzing data. In fact, you'll probably be doing much more statistics and number crunching in biological science than in PhD level computer science, which tends to be in some theoretical study less focused on crunching of numbers. And biologist just commands respect. There's just no similar honorary title for computer scientist, and although PhD is different, it's hard to not associate CS with a factory-like undergraduate program, churning out low-skilled CS majors.
Your Ph.D. will be the name of the department you graduate from, but that says little about the work you do. I work in a Department of Anatomy, and some of our students do purely physics work using MRI technology to quantify signal intensities based on a chemical marker. Their Ph.D. will be in Anatomy, but their work will be in Applied Physics.
Your C.V. should show your entire career trajectory, not just a single line with some name of a department on it. In fact, many people simply omit the department name because it is unnecessary. When you apply for jobs, you will write several letters: a general cover letter, a letter introducing your research, a letter proposing future research potential. You will not be judged on the name of your Ph.D., you'll be judged based on how cogently you can write a letter.
In addition, your P.I. may get a primary appointment in one department, but he can also request secondary appointments to OTHER departments, say in Biostatistics, Neuroeconomics, Computational Statistics, etc.. This might benefit him as well, by giving him a stronger association with potential collaborators. One of our professors has 'dual-appointments' in four departments, including Anatomy, Electrical Engineering, and Chemistry, because their research reflects all of these disciplines.
Personally when I'm interviewing for staff (in the UK), I only look at what university they went to, not what they studied.
I'm not sure what other countries are like, but over here everyone under 30 years old has a degree, so the only interest I have in their university experience is whether they went to a "Red Brick" (Ivy league equivalent) or a "modern" university (re-branded technical college or polytechnic)
The fact you have a degree shows your ability to learn. What you learned in the past 4 years of University is of less interest to me compared to your potential to learn over the next 30 or 40 years of your career.
I personally value the fact someone even managed to get in to Oxford or Cambridge higher than someone else's 2:1 "degree" from some "university" I've never heard of in the North of England. Sadly this is what happens when governments devalue higher education with misguided targets such as 50% of the population must have a degree.
Philosopher (n) - a wise person who is calm and rational; someone who lives a life of reason with equanimity
I have been actively hiring PhDs to do analytics work for financial services for the last two years. We primarily use machine learning techniques to develop risk management tools. We prefer the applicants to have a PhD, although industry experience can make up for the lack. In general, however, we do not specify that the PhD come from a specific field. Indeed, we have a bio-informatics PhD in our group, and we have interviewed several others. I myself come from a physics background, and others came from engineering, cognitive science, etc. We like to interview candidates who have experience in machine learning or computer science, but even those without such experience are considered if they have shown strong analytical skills during the course of their research.
In the world of business, who you know is much more important. Your friends and parents are far more important then the kind of Ph.D you have.
Rhetorical nonsense.