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the ability to quickly learn new things and work independently, along with previous research experience in at least one of the following areas: 1) statistical genetics/genomics/omics, or 2) deep/machine
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neuroscience. The position is open under specific projects as well as general research involving the application of methods from theoretical physics, mathematics, and machine learning with the goal to understand
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
the development and implementation of machine learning models Special Physical/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and Services click here Quick Link https
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large sample libraries; performing in-depth analysis of proteins, peptides, and small molecules in beef and pork products that vary in consumer quality; and applying machine learning techniques to predict
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. The project takes an explicit social science approach and aims to use Machine Learning and Social Network Analysis methodology to 1. analyze the current and developing opinions of new clean energy technology
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Toggle navigation Your VUSM Current Students Postdocs Residents Basic Sciences Faculty Affairs Clinical Faculty Affairs Alumni Patients A-Z Directory VUSM Catalog School of Medicine Vanderbilt
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Apply Now How to Apply To be considered for this position, applicants should submit their materials to Interfolio https://apply.interfolio.com/179185 Cover letter (1-2 pages) which includes a
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for postdocs. UNLV currently employs postdoctoral scholars across a wide range of disciplines. Learn more about UNLV's postdoctoral scholars. MINIMUM QUALIFICATIONS This position requires a PhD in Chemistry
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research managers, with expertise in data science, machine/deep learning, biomedical informatics, trustworthy AI, and health-related applications. The research group has an established track record in
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hardware Experience with atomic layer deposition and process development Experience with thin film and materials characterization Strong background in computational materials science and machine learning