Postdoctoral Researcher in Fair Machine Learning at Harvard & UCSD
Location: Cambridge, Massachusetts
Internal Number: 10575
School: Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area: Electrical Engineering
We invite applications for a postdoctoral researcher in fair machine learning in healthcare to work with Prof. Flavio Calmon at Harvard SEAS and Prof. Berk Ustun at UCSD. Applicants will broadly be expected to work on research related to fairness, privacy, interpretability for machine learning in healthcare (e.g., challenges related to precision medicine, personalization, and communicating uncertainty), information theory, and optimization.
Applicants will be expected to lead cutting-edge research, supervise with PhD students at Harvard and UCSD, and participate in research collaborations with top-tier medical institutions across the US. Applicants will also have the opportunity to develop their own research agenda and start collaborations with faculty at UCSD and Harvard.
This is a joint postdoctoral fellowship at Harvard and UCSD. The position has significant flexibility. Applicants should plan to reside in San Diego but will be able to spend significant time in Boston to advance collaborations at Harvard (e.g., spend the academic year at SD and the summers in Boston, or spend one semester in Boston). The target start date is June 2022. The position is funded for two years, with a potential extension for a third year.
About Us Flavio Calmon is an Assistant Professor of Electrical Engineering at Harvard's John A. Paulson School of Engineering and Applied Sciences. Before joining Harvard, he was the inaugural data science for social good post-doctoral fellow at IBM Research in Yorktown Heights, New York. He received his Ph.D. in Electrical Engineering and Computer Science at MIT. His main research interests are information theory, inference, and statistics, with applications to fairness, privacy, machine learning, and communications engineering. Prof. Calmon has received the NSFCAREER award, the Google Research Faculty Award, the Amazon Research Award, the IBM Open Collaborative Research Award, Harvard's Lemann Brazil Research Fund Award, and a Harvard Commendation for
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