51 parallel-processing-bioinformatics Postdoctoral research jobs at Princeton University in United States
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attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH Silvio O. Conte Center on the "Cognitive Thalamus". The successful
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areas as demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine learning
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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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multi-year appointments. Experience with one or more of the following is a plus: metabolomics, bioinformatics, and/or bacterial genetics. Applications from members of groups historically under-represented
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of design, computation, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and
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, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational
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demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine learning/computer science
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Library and to a wide range of activities throughout the University. This position is subject to the University's background check policy. Appointments are for one year. Applicants cannot be in the process
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with members of the Geosciences Department. One or more Hess Fellows may be appointed. Applicants must have or be in the process of completing a Ph.D. and must have less than two years of post-Ph.D
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of this research is assessing the fitness of geospatial indicators to inform conceptual and policy-relevant understanding of vulnerability processes for disaster risk reduction and climate adaptation. The researcher