Training for diverse career paths

In a recent SfN webinar Developing a 21st Century Workforce, moderated by Katja Brose, speakers Huda Akil, Elisabeth van Bockstaele and Adrienne Fairhall discussed training for career paths beyond academic science, the importance of interdisciplinary training, and strategies for programs and individual students to gain opportunities to enhance students’ quantitative backgrounds. At UW, UWIN, the Computational Neuroscience program and the CSNE aim to provide students with these training opportunities and to give exposure to an increasing range of job openings in neurotechnology companies. To help plan for such a future direction, it is interesting to look at the hiring criteria for jobs at a new start-up and CSNE partner, ArianRF:

  • Solid knowledge in neuroscience
  • Experienced with neural signal acquisition
  • Experience with EEG/ECoG
  • Solid knowledge in signal processing/ statistical signal processing
  • Knowledge in machine learning and computational neuroscience
  • Motivated and self-driven: willing to be a core person and “go to guy” in a start-up company.