This position is for a Postdoctoral Scholar position. Applicants will broadly work on algorithmic fairness in healthcare under the supervision of Prof. Flavio Calmon at Harvard SEAS and Prof. Berk Ustun
at UCSD. There is flexibility to work on theory or method development related to topics like the fairness in personalization, the use of protected attributes. This is a joint appointment between UCSD and Harvard.
This is a joint postdoctoral fellowship at Harvard and UCSD with a lot of flexibility. You may choose to reside in Boston or San Diego, or split your time between the cities (e.g., spend the academic year in San Diego and the summers in Boston). The earliest start date is September 2021, though a later start is fine. The position is funded for two years, with a potential extension for a third year. The baseline salary for this position is 60k.
We will review applications starting on March 15, 2021. Applications will be accepted after this deadline until the position is filled. Please see application details in the following link: https://apolrecruit.ucsd.edu/JPF02646
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 NSF CAREER 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 “Extraordinary Teaching in Extraordinary Times” for his undergraduate signal processing course. For more information, please visit: http://people.seas.harvard.edu/~flavio/
Berk Ustun is an incoming Assistant Professor at the Halıcıoğlu Data Science Institute at UC San Diego. His research lies at the intersection of machine learning, optimization, and human-centered design.
Specifically, he is interested in developing methods to promote the adoption and responsible use of machine learning in medicine, consumer finance, and criminal justice. Prior to his appointment at UCSD, Ustun held research positions at Google AI and the Center for Research on Computation and Society at Harvard. He received a PhD in Electrical Engineering and Computer Science from MIT, an MS in Computation for Design and Optimization from MIT, and BS degrees in Operations Research and Economics from UC Berkeley. For more information, please visit https://www.berkustun.com.
Applicants must have a PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, Data Science, Bioinformatics (or a related discipline) or be confident of its completion by the time of the start of this position.
Experience in machine learning, an interest in algorithmic fairness, and expertise in at least one of the following areas is preferred: optimization, statistics, causal inference, and information theory. Prior experience in healthcare is preferred, as is an ability to code in Python. Candidates with a commitment to support diversity, equity, and inclusion in an academic setting are welcome.