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that require novel approaches. The successful candidate will possess a doctoral degree with expertise in molecular biology, experience with in-vivo and in-vitro models of inflammation testing, and experience
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Biology. The Laufer Center is a hub for research in physical and quantitative biology at Stony Brook University. Our aim is to advance biology and medicine through discoveries in physics, mathematics and
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individuals with a Ph.D. and experience in molecular biology, biological sciences or pharmacology are encouraged to apply. The project is multidisciplinary, using a variety of techniques and approaches
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metabolites. Our group integrates these data with a combination of computational biology, machine learning, and statistical approaches. This position will translate, develop, and deploy genomics pipelines
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on different disease conditions, with the idea of developing megavitamin therapies for metabolic and age-associated conditions. We will be using a combination of systems biology approaches (CRISPR screens
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Details Title Post-Doctoral Fellow in Chemistry and Chemical Biology School Faculty of Arts and Sciences Department/Area Chemistry and Chemical Biology Position Description We are seeking a highly
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biology and animal models. Typical Hiring Range Commensurate with Experience II. POSITION INFORMATION Posting Number P010042 Job Open Date 05/20/2024 Job Close Date Part-time / Full-time PF Post Doc Full
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., Tennessee Valley Authority, and Oak Ridge National Laboratory. Qualifications Requirements: Must have successfully defended and submitted dissertation by hire date, Ph.D. in chemistry or chemical biology
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to be a full-time researcher dedicated to investigating diseases of our field. The applicant's area of expertise may include, but not be limited to, Bioengineering, Cancer Molecular Biology, Database Bio
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Postdoc in CRISPR Meta-Analytics and AI for Therapeutic Target Discovery and Priotisation (OT Grant)
solutions. Situated in the Computational Biology Research Centre of HT, the Iorio Lab operates at the intersection of biology, machine learning, statistics, and information theory. Our goal is to comprehend