(The lab is not currently looking for undergraduate researchers!)
As for graduate students, we’re rarely 100% certain our lab will be accepting new students in any given year. It depends, as much often does, on funding; if funding for the lab is looking good we’ll probably be looking for more students. However we’re always happy to have students collaborate with the lab and join our lab meetings, regardless.
The barrier is never lack of research projects, but often lack of time. Voytek prioritizes mentoring, and wants to make sure he has enough time to closely work with everyone in the lab.
If you are interested in applying as a PhD student, note that Voytek accepts students from either the Cognitive Science or Neurosciences PhD programs. You can find application information for each here: Cognitive Science; Neuroscience. However in neither case are students accepted to join a lab directly; rather students are accepted by an admissions committee to join the program to which they applied. During the first year of training, PhD students rotate between 2-3 different labs for about 10 weeks each. This is to give them some breadth of experience and let them get to know their prospective PhD mentor. At the end of the first year, students then speak with their prospective mentor to officially join a lab.
Do not apply to the UC San Diego Neuroscience and/or Cognitive Science programs because they are “prestigious”. While this is not to say that desiring prestige is wrong, it’s not the best reason to pursue a PhD somewhere. The best place to pursue a graduate degree is the place that maximizes the following (weighted according to your personal taste):
Prioritize academic interests and happiness. In short: if you’re not happy, your work will suffer for it. And “prestige” isn’t going to make you laugh, go to lunch with you, or help you when things get tough.
With regards to specific skills/knowledge before entering a lab, there are a few especially important skills to know:
Our lab is Python- and git-heavy, so we recommend learning or brushing up on those skills. You can learn Python by working through the materials from lab PhD alumnus Tom Donoghue’s Introduction to Python class (COGS18) and Voytek’s Data Science in Practice class (COGS108). You can learn git here.
A lot of people ask Voytek about his industry time working as a data scientist, and what they need to do to break into the field. When I was on the hiring side, I always looked to see some portfolio showing evidence that the applicant had done something. So many people would approach me with a resume and say, “here are the classes I took,” but, honestly, so did tens of thousands of other people so why should we hire you?
Thus my advice is to do something.
brainSCANr was a huge help for my data science career for that reason: it was clear evidence that showed we could conceive of an idea and see it through to completion. Even something silly like this analysis and visualization of the “best rap vocabulary” shows that the author can think of a neat idea, run a fun analysis, complete the project, write it up, and visualize it.
This is partly why so many aspects of the UC San Diego undergraduate data science major include projects.
As for my data science toolkit:
Also, Python is used extensively for non-stats/non-scientific programming, so if my students learn Python they have a marketable skill should they decide to not pursue a career in academia.