132 high-performance-quantum-computing Postdoctoral positions at Princeton University
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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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behavioral paradigms and combined with computational approaches. We are seeking an extremely motivated postdoctoral researcher with background in human or monkey electrophysiology. Studies will include
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are for one year with the possibility of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year appointments. Please include a cover letter, CV and
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strong commitment to excellence in education are encouraged to apply. A Ph.D. is required. Postdoctoral appointments are for one year with the possibility of renewal pending satisfactory performance and
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, with a possibility for renewal contingent upon satisfactory performance and available funding. Applicants must have a Ph.D. in Geosciences or a closely-related field. Applicants should include a cover
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The Department of Computer Science at Princeton University is seeking applications for postdoctoral or more senior research positions in theoretical computer science and theoretical machine learning
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Fellows Program. The Program recognizes and supports outstanding early-career scientists who can make important research contributions in the areas of ecology, evolution, and/or behavior, while also
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performance and continued funding; those hired at more senior ranks may have multi-year appointments. These positions are subject to the University's background check policy. The work location for this position
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positions are pro-rated accordingly. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
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computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models of reinforcement learning in the brain and