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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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, engineering, physics, or similar fields by the expected start date. Additional Qualifications Applicant should ideally have some experience in electric power systems, artificial intelligence, and optimization
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medicinal chemistry and lead optimization. Lead the development of assays for small molecule discovery Miniaturize and adapt cell-based and biochemical assays to automated screening systems Propose and
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Together, these research directions seek to reimagine how buildings and cities operate—optimizing energy use, enhancing human well-being, and reducing carbon emissions at scale. We are seeking multiple
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. Troubleshoot imaging challenges and assist with image analysis as required. Meet with investigators to help design experiments, determine the appropriate technologies, and identify optimal workflows for a wide
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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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multidisciplinary team members to optimize experimental protocols and analyze data. Publish research findings in peer-reviewed journals and present results at conferences and seminars. Mentor graduate and
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seeking a highly motivated postdoctoral researcher to play a key role in optimizing the performance of the Rubin Observatory system. Our near-term goal is to optimize the performance of the Rubin