103 machine-learning "https:" "https:" "https:" "U.S" Postdoctoral research jobs in United States
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worldwide and BNL is responsible for data compilation in North America. In order to make full use of the data in EXFOR, experience in data science, machine learning (ML) and applications of artificial
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at the interface of biostatistics, machine learning, and biomedical data science. This mentored postdoctoral position is designed to support the development of an independent research trajectory in methodological
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of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL
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sciences, including technologies that are driving the generation of massive datasets, the exponential growth of publicly available data, and revolutionary approaches in statistics, machine learning, and
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multi-omic sequencing, network biology, and machine learning to identify actionable biomarkers and therapeutic vulnerabilities. The successful candidate will work at the interface of computational
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Organization U.S. Department of Energy (DOE) Reference Code DOE-Scholars-2026-EM How to Apply Click on Apply below to start your application. Application Deadline 3/31/2026 8:00:00 AM Eastern Time
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Scholar Salary range: A reasonable salary range estimate for this position is $66,737 - $80,034 based on level experience. The posted UC academic salary scales (https://www.ucop.edu/academic-personnel
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The Department of Biostatistics at the University of Washington has an outstanding opportunity for a postdoctoral scholar. The postdoctoral scholar will develop statistical machine learning and artificial
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https://pubs.acs.org/doi/full/10.1021/acssuschemeng.5c0419 The successful candidate will be able to: Work safely and independently in a laboratory setting Learn new techniques and protocols Plan and
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Computing Applications group in CSD has an immediate opening for a Postdoctoral Research Associate to design, develop, and deploy machine-learning and high-performance computing workflows, algorithms, and