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. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a strong background in this area, as well as a genuine interest in continuing such work
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Details Title Postdoctoral Fellow in Energy System Optimization and Digitization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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Harvard Office of Technology Development (OTD): Business Development Fellowship Deadline Month: January Description: This year-long program provides current Harvard graduate students and
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Electrical Engineering or any field with relevant skillsets will be considered. Currently, expertise in digital signal processing, nonlinear optics, local probe microscopy (STM), statistical physics and on
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focus on accelerating energy system transformation. The position will be housed in the Salata Institute for Climate and Sustainability as part of a broader research initiative on enabling the transition
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procedures, and electrophysiology. The candidate is expected to operate independently within defined protocols and contribute to troubleshooting and optimization of experimental systems. Basic Qualifications
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Electrical Engineering or any field with relevant skillsets will be considered. Currently, expertise in digital signal processing, nonlinear optics, local probe microscopy (STM), statistical physics and on
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at the interface of neural engineering, bioelectronics, and physiology. The role focuses on developing and evaluating sensing technologies for peripheral nerve and organ interfacing, with an emphasis on in vivo
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Institute for Climate and Sustainability as part of a broader research initiative on enabling the transition to a deeply decarbonized and reliable energy system. The Postdoctoral Fellow will work closely with