80 parallel-processing-bioinformatics-"Multiple" Postdoctoral positions at Princeton University
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simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use of laminar/neuropixel probes and electrical microstimulation to study
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-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning
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. Previous experience in computational modeling of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based on rank. Positions at the postdoctoral
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the following areas as demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine
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to coastal sea level variability and relevant physical processes (e.g. ocean warming and mass redistribution); 2) conducting sensitivity analyses to identify the roles played by model forcing, horizontal
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significant independence in selection of their research directions within their departments and can acquire a breadth of expertise by working with multiple faculty members.We value building a culturally diverse
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patterns and processes that have shaped biological history across deep timescales. The ideal candidate will have a background in phylogenomics and bioinformatics of squamate reptiles; the largest group
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of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility
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: 279395597 Position: Postdoctoral Research Associate Description: The condensed matter spectroscopy group at Princeton University invites applications for multiple Postdoctoral Research or more senior
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-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning