-
the project directors and collaborators to develop data-driven and economically grounded frameworks for understanding how AI-enabled control, optimization, and market design can support large-scale
-
. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
-
/Area Computer Science Position Description Accepting applications for postdoctoral position in Reinforcement Learning, Probabilistic Methods, and/or Interpretability. Information on the lab can be found
-
; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
-
Details Title HMS - Postdoctoral Fellow in Biomedical Informatics (Park Lab) School Harvard Medical School Department/Area Biomedical Informatics Position Description The candidate will have the
-
Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
-
effect prediction. The fellow will work under the mentorship of Dr. Alex Luedtke and collaborate with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy