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Requisition Id 16140 Overview: We are seeking a Postdoctoral Research Associate who will focus on data center thermal management technologies. This position resides in the Multifunctional
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 1 hour ago
electrophysiology to assess mechanisms of drug effects on cardiac and neuronal ion channels critical for safety evaluation. Additionally, the research will include advanced statistical modeling for data analysis and
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to apply for a faculty or staff position, please review this tip sheet . The Department of Informatics and Health Data Science has an exciting opportunity for a full-time Postdoctoral Scholar to work on the
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portfolio of data science-based projects which are aimed at assessing the near- and long-term health outcomes for a cohort of Service members who have sustained traumatic extremity injuries. You will gain
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information about AbbVie, please visit us atwww.abbvie.com . Follow @abbvie onX ,Facebook ,Instagram ,YouTube ,LinkedIn andTik Tok . Job Description Program Overview AbbVie needs outstanding individuals willing
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Job Posting Title: Postdoctoral in Cognitive and Behavioral Data Science ---- Hiring Department: Department of Psychology ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40
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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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Professor Fei Lu and Bloomberg Distinguished Professor Mauro Maggioni on topics including mathematical foundations of data science and statistical/machine learning, with an emphasis on inverse problems and in
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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postdoctoral research associate to advance the state of scientific AI by addressing cross-cutting challenges in data readiness for AI to enable scalable, reproducible AI workflows on leadership-class systems