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. This opportunity will prepare candidates for a range of competitive positions in academia or industry that involve computational biology/chemistry, machine-learning for biological or chemical data, metabolism, and
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: 285829795 Postdoctoral Research Associate Location: Princeton, NJ Salary Range or Pay Grade: PDRA: $65,000-$67,000 ARS: $66,000 - $75,000 Description The Department of Ecology and Evolutionary Biology has
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University is seeking a full-time Postdoctoral Research Associate. The Atkinson lab focuses on using protein engineering and synthetic biology approaches to control gene expression and metabolism in cells
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demonstrated through at least one first-author publication: machine learning/computer science, computational biology/bioinformatics, cheminformatics. Individuals should have or be expected to have a PhD with
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, information theory, computational biology and image processing. Applicants must have (or expect to have at the time of appointment) a PhD. The work location for this position is in-person on campus at Princeton
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references. Essential Qualifications: Ph.D., M.D., or equivalent is required. Applicants should have training and a significant track record in one of the following areas: -computational biology -computer
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The Department of Molecular Biology at Princeton University currently has research positions available at the postdoctoral and more senior research levels in the areas of biochemistry, biophysics
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at Princeton University currently has research positions available at the postdoctoral or more senior research levels in the areas of neuroscience, psychology, molecular biology, biochemistry, physics
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to have a Ph.D. or equivalent in evolutionary biology, genomics, or related fields. Candidate must have excellent computational and bioinformatic skills as well as strong experience with next-generation
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training and a significant track record in one of the following areas: -computational biology -computer science -electrical or computer engineering -genomics -neuroscience -population genetics / genomics