Just finished a 2 hour workshop for #sysmus20 titled "Turning Your Values into Value" aka a crash course in getting non-academic work for grad students in #musicscience I'll try to summarise what I said (all my opinions) in case anyone else is interested in the workshop!
TLDR Most grad students won't work in academia, but that's OK and I really wanted to brand of the workshop not to be this doomsday fear inducing stuff I see on my twitter feed every day. Of course the competition is stiff, but I just can't stand more doomsdaying.
There were five short (but intense) slide decks (should have been less but had to include it all). First was to show how step number one of getting work is to figure out why someone would even give you salaried job in the first place. We start with mapping out
how academia "works" (what's valued and why) then transitioned that mental model to investigate learning about companies. This sets the stage for really trying to be empathetic about why you should be hired by others. Note I say others as in other people and not
treating companies like faceless corporations (some are) but rather collections of people. You gotta show you get how it all works to be taken seriously. Next we talked about online presence and why I think that's important. Basically (like said in old blog) you
want people to know you before they meet you. Are you who you say you are? Can you point to examples of your ability? Would you be a good fit for the company culture (for better or worse)? It's always more important to show rather than tell what you can do. You say
you can program? Point to a blog where you talk about your code. Say you're a good communicator? Point to example of you talking or writing clearly. The idea is to make life easier for the sceptical hiring manager. We next talked about
Networking and why it's better IMO opinion to think of it as making more friends and why the best networking you can do is people near your academic age. Really tried to make it clear to respect other's time and expertise and that many people do want to help.
We then had a session on translating your work which was more an exercise in empathy and thinking what you actually want to convey in describing your research (talking in a way that conveys the magnitude and scope of your ability)
Lastly we talked about how to prepare for #datascience . IMO doing a PhD really prepares you for the science part of data science and all the technical infrastructure to deal with the big amounts of data since the 1980s can be learned. So try to learn tools in #gradschool that
will make your life and research easier down the road no matter what you do. Learn a language you can get help with given the flexibility you have in grad school compared to working. Then if you want to apply for work in #datascience we talked about how the idea of a portfolio
allows you to put it all together by putting your money where your mouth is.
Of course there are things I'd change for next time but would love to give this workshop again. Already have some great feedback that has made my day <3.
The slides are kind of ugly now (more like place holders than the decks I used to make) but it works well fully online.
Grateful to be able to have shared what I've learned with the new generation of #musicscience grad students.
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Looks like this #musicscience pre-print showing 0 effect between musical training and cognitive abilities has been accepted at Memory and Cognition and is getting some press.
IMO moments like this are a great chance to just remind people that you don't
need the backing of Science™ to justify what you find meaningful. In a lot of ways, it's liberating to nullify this relationship to help focus conversations about #music to other reasons like how it's a great way to explore the many ways to be human, it's a way to learn
about other cultures, it's a way to form meaningful relationships with others, + things that are not by-products of traits that are valued by a society that wants productivity over all other things. Talking with my #musiceducation colleagues, I know the smarter~musical training
A few months ago I wrote a very long blog for @CommitteeSysmus on advice that I wish I would have heard when I was a graduate student about getting a non-academic job.
I'll thread the major points below because it's a long one (4K words)
There are a lot of resources on how to keep going on in academia, but as we all know, we can't all immediately go from PhD to more academia (AND this was all originally written pre-COVID) but there's not a lot of good resources to help people prepare for that as a student.
So I wanted to just pass on many words of wisdom that I think I would have found helpful a few years ago (esp since my first job out of PhD was helping people land junior #datascience jobs) and not just say what to do (ewww) but rather my thoughts on why.