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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
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. 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
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team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/erapid-multiplexed-electrochemical-sensors-for-fast-accurate-portable-diagnostics/. What you’ll
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applicants for a postdoctoral fellow position in the Laboratory of Systems Pharmacology (LSP; https://labsyspharm.org/ ), part of the Harvard Program in Therapeutic Science, at Harvard Medical School in Boston
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an environment that is diverse, inclusive and respectful. Learn more about our lab here: https://bioniclab.seas.harvard.edu/ We are recruiting fellows from diverse backgrounds interested in solving tough problems
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fellow with a Ph.D. in electrical engineering, applied mathematics, or related field. Candidates will perform research on agentic AI, foundational modeling, optimization, and control of multiagent
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the Harper lab at Harvard Medical School in Boston, Massachusetts. Our laboratory works at the intersection of protein and organelle quality control, the ubiquitin system, and autophagy and its role in
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science; quantum many-body physics; quantum precision measurements and fundamental physics; quantum metrology, sensing, and control; and quantum chemistry and materials science. Fellowships are awarded for a
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integrates three synergistic research thrusts: Advanced thermal storage and sensing materials Intelligent, building-scale integration of sensing and control systems Cooperative, urban-scale energy management
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models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization