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at https://puwebp.princeton.edu/AcadHire/position/40281 and submit a current curriculum vitae, research statement, and a cover letter. Contact information for three references is required. To learn more
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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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biophysics -experimental and/or computational genomics -computer science, statistics, and/or machine learning with applications relevant to genomics -bioinformatics -population genetics / genomics
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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vision and novel applications of machine learning. Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL dialect is preferred. Apply online at https
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across the broad areas of Statistics and their applications in machine learning. The ORFE department is part of the School of Engineering and Applied Science which is pursuing several initiatives in
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. Responsibilities Application of Domain Expertise: Maintain strong command of AI and machine learning concepts, including underlying science, math, and algorithms; stay current through reading publications, reviewing
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learning to reconstruct perceived information from functional MRI in real time. For more information on Professor Norman’s lab, see https://compmem.princeton.edu. Questions should be directed to Professor
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collected from these studies, subject recruitment, and some administrative work. Depending on qualifications/interest, the research specialist may also assist with developing computational models of learning
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been filled. Contact information for three references is required. To learn more about CITP's fellows' program please visit our website (https://citp.princeton.edu/programs/fellows/). CITP is committed