303 computer-programmer-"Multiple"-"U"-"Humboldt-Stiftung-Foundation"-"Prof"-"O" positions at Harvard University
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physics, biology, economics, computer science, AI, statistics, and other disciplines Appl Deadline: 2025/11/15 11:59PM (posted 2025/08/03, listed until 2025/11/15) Application Description: Apply
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Welfare Work/Life and Wellness Retirement Tuition Assistance Program Tuition Reimbursement Professional Development Commuting and Transportation Harvard Facilities Access, Discounts and Perks Department
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or computational research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing of grants and manuscripts, participate in teaching and mentoring of lab members as
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contribute to technical deliverables and help to plan for technology translation. Basic Qualifications PhD in engineering, biomechanics, or a related field. Additional Qualifications Interest in
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Interest in learning and strengthening existing skillsets Strong technical and programming skills, familiarity with current deep learning techniques, with a focus on computer vision Contact Information
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assessment, and ambulatory behavioral assessments to precisely track brain and cognitive change over short intervals. The program of research seeks to understand individual differences in aging trajectories
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applications to teach in the Sophomore Tutorial program. Tutor positions are open to advanced graduate student and postdocs/PhD-level early career instructors with prior teaching experience. Sophomore Tutorial
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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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. Must enjoy working in a fast-paced environment, work well under pressure and be able to prioritize work. Excellent computer skills, including word processing, spreadsheet and database management
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research associates to develop and apply theoretical and computational approaches to study complex cell biological systems. The emphasis will be on combining statistical inferences and biophysical modeling