230 computer-programmer-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at Harvard University
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Details Title Postdoctoral Fellowship in Power and AI Systems School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science/ Electrical Engineering
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to detail and organization skills Interest in learning and strengthening existing skillsets Strong technical and programming skills, familiarity with current deep learning techniques, with a focus on computer
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Type: Postdoctoral Location: Cambridge, Massachusetts 02138, United States of America [map ] Subject Areas: Computer Science / All areas Statistics / Statistical Physics , Applied Statistics
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the use of Microsoft Office applications (e.g., word-processing, spreadsheets, databases), internet applications, electronic mail/calendaring, etc. Ability to access and modify data in Computer-Aided Design
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. Responsibilities include coordination and collaboration with Advanced Graduate Program directors to grow the strategic direction of Advanced Graduate Education at HSDM, to maintain high standards and compliance with
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Fund team to plan solicitation strategy, including brainstorming new opportunities and concepts Liaise with University?s principal and major gifts proposal team to leverage existing formats and content
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@seas.harvard.edu . Applications will be reviewed on a rolling basis. Basic Qualifications A Ph.D. in Mathematics, Computer Science, or a related field, by the start of the appointment. Additional Qualifications
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rolling basis. The position will remain open until filled. Basic Qualifications A Ph.D. in Mathematics, Applied Mathematics, Computer Science, or a related field, by the start of the appointment. Additional
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with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics, computer science, engineering, or related fields. Experience in relevant research
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be