1/11/2024 0 Comments Cogs sci ucsd![]() I'd say this is true for all majors, but this is more true of CogSci than engineering. It also means that you have to do a lot of your own work developing your understanding of your interests and career goals without a lot of examples of people who have gone before you to work off of.ĬogSci is not the kind of major where you can just graduate UCSD CogSci and get a job, it depends a lot on your extracurriculars, internships ect. Research allows you to develop a skillset that positions you to do really cool, bleeding-edge work and develop a specialization very early on in your career. ![]() After people realize most data scientist aren't going to change the world, demand is largely going to go down but if you really commit to the field and are in the top tier of knowledge and skills you'll be changing the world - and making piles of money - for decades to come.Īll of which is to say, the environment at UCSD - at least as I know it, which includes Cog Sci - is much more geared towards research (and grad-school prep) than get-a-job-with-a-bachelor's prep. Data science is the new hotness and for probably 5 or 10 more years everyone is going to want to hire them because they think they're going to change the world. Now, the one career track that you probably could dive right into with a Cog Sci ML degree is data science. Lots of doors are open, but you have to build the flooring that allows you to walk to and through them, if that makes sense. This kind of research experience is gold for graduate school it can be gold for a career as a bioinformaticist or a quantitative finance analyst as well, but there's no established path between those points so you'll have to take charge and build your resume with that in mind. The other specializations might not prepare you for quite as much interdisciplinary work, but there are a number of extremely well-known and kickass neuroscience labs across campus, as well as interaction design labs so research is still very much a primary means of developing experience in the other Cog Sci specializations. Particularly from the machine learning angle, having a background in both statistics and programming means that many research labs on campus will be interested in you volunteering for them, even if you're not quite in the same niche as them.įor instance, as a Cog Sci student you might find yourself volunteering for a lab that builds exoskeletons that the paralyzed can control with their brain waves in order to walk, models protein dynamics for the development of cancer drugs, analyzes the Indian economy to alleviate poverty, or something completely different because your skills meet the analytical requirements of a lot of labs even if your coursework doesn't immediately match up. ![]() Instead, what Cog Sci (and UCSD more broadly) will give you is the environment of a very powerful research institution and the tools to become a part of the research ecosystem. This isn't a bad thing (especially if you want to go to grad school!), but it's something you need to prepare for because especially in Cog Sci there really aren't pre-built paths for you to follow that get you from taking classes, doing homework, and getting good grades to doing job X with your bachelor's. The important thing to understand about UCSD as a whole is that it's not particularly geared towards job-preparation the interest of the university aligns much closer to what we'd probably think of as grad-school preparation.Įspecially outside of engineering - although perhaps within engineering too, I'm not familiar with that side of the house - the university assumes (this is a simplification, but I don't think a huge one) that the average student is more interested in pursuing a graduate degree at a competitive university than taking their bachelor's and going right into the workforce.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |