Postdoc Position Announced at Foundations of Data Science Institute (FODSI)

Foundations of Data Science Institute (FODSI), Posted: November 17, 2022

The Foundations of Data Science Institute (FODSI), funded by the National Science Foundation TRIPODS program, is announcing a competitive postdoctoral fellowship. FODSI is a collaboration between UC Berkeley and MIT, partnering with Boston University, Northeastern University, Harvard University, Howard University and Bryn Mawr College. It provides a structured environment for exploring interdisciplinary research in foundations of Data Science spanning Mathematics, Statistics, Theoretical Computer Science and other fields.

We are looking for multiple postdoctoral team members who will collaborate with FODSI researchers at one or more of the participating institutions. These positions emphasize strong mentorship, flexibility, and breadth of collaboration opportunities with other team members -- senior and junior faculty, postdocs, and graduate students at various nodes around the country. Candidates are welcome to contact potential FODSI mentors to identify common interests. Furthermore, postdoctoral fellows will be able to participate in workshops and other activities organized by FODSI.

The fellowship is a one-year full-time appointment, with the possibility of renewal for a second year (based upon mutual agreement) either at the same or at another FODSI institution. The start date is flexible, although most appointments are expected to start in summer 2023. Candidates are encouraged to apply to work with more than one faculty mentor at one or more participating institutions (in-person mentoring is preferred, but remote options will be also considered). The applicants should have an excellent theoretical background and a doctorate in a related field, including Mathematics, Statistics, Computer Science, Electrical Engineering or Economics. We particularly encourage applications from women and minority candidates.

The candidates should apply by December 15 for full consideration.