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. https://pai.seas.harvard.edu The postdoc is intended for one year but we anticipate there will be funding to potentially extend it to a second year. The postdoc will receive a generous salary as
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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oceanography of the Southwest Greenland shelf as part of the Overturning in the Subpolar North Atlantic Program (OSNAP, www.o-snap.org ). The postdoc is expected to work with a variety of data (moored, vessel
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fabricating nanoelectronics and flexible electronics. An extensive experience in cleanroom nanofabrication is required. The postdoc is also expected to collaborate with other researchers to apply
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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. Basic Qualifications: Applicants should have least 2 years of directly applicable postdoc experience Additional Qualifications: Prior experience with random matrix theory, statistical inference, active
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with more limited time-course information. Basic Qualifications Applicants should have least 2 years of directly applicable postdoc experience Additional Qualifications Prior experience with random
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-related conditions or any other characteristic protected by law. Minimum Number of References Required 3 Maximum Number of References Allowed 3 Keywords postdoctoral; postdoc; fellow; social science
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Ph.D. in a relevant field by the time of appointment. The postdoc will be based at the Harvard University Herbaria (HUH) and will have access to all the resources available through the Department of OEB
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nanofabrication is required. The postdoc is also expected to collaborate with other researchers to apply nanoelectronics and flexible electronics in biological and medical research. Basic Qualifications: Ph.D. in a