108 computer-programmer-"https:"-"Inserm"-"https:"-"https:"-"https:"-"U.S" Fellowship positions at Harvard University
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, Mechanical Engineering, Computer Science, or a related field for biomechanics and assistive robotics is required by the time the position starts. Additional Qualifications Some background in coding, controls
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Native American Program, and in collaboration with regional and national Indigenous community partners, the fellow will assume mentored responsibility for: (1) advancing research projects, analyzing
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cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical data across multi-institutional research networks, with a focus on the analytical and
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will involve investigating the physiological and functional variation of plants using spectroscopy and will include greenhouse work, field work, plant phenotyping, computational analyses of hyperspectral
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to appoint one or more postdoctoral fellows beginning in November/December 2025. We are looking for candidates with interests in the use of atomic cavities and atomic arrays for quantum computing. Candidates
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Details Title Postdoctoral Fellowships in Networking Support for Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science Position
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Requirements Strong computing and strong background/expertise in clustered data, survival data, causal inference or measurement error are desired. Strong written communications Additional Information: Per
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history that has taken place largely in Pakistan, and plan to return to Pakistan upon completion of the fellowship. Basic Qualifications Applicants must hold a PhD. Additional Qualifications Special
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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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sophistication, including strong statistical skills and comfort with large-scale or complex data. Experience with computational text analysis, such as NLP methods, historical text processing, topic modeling