73 computing "https:" "https:" "https:" "UCL" Postdoctoral research jobs at Duke University
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, United States of America [map ] Subject Areas: Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Computer Science Machine Learning Appl Deadline: none (posted 2025/08
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regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. The Postdoctoral Associate will conduct research in statistical machine learning and
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primary benefit. This postdoctoral appointment is part of the Duke University Aging Center’s NIA-funded T32 Postdoctoral Research Training Program. This multidisciplinary program is focused on developing
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, evidence-based practice, and interdisciplinary collaboration to lead the future of nursing. Our nursing program stands as a leader in healthcare education, earning #1 in the nation for Best Bachelor
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international and regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. We are recruiting a creative, rigorous Postdoctoral Research Scientist
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systems, social sciences, epidemiology or other health-related fields. Demonstrated proficiency through previous developed analytical codes with R Language for Statistical Computing and/or Python The ideal
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) Experimental investigation and computational model simulation of laser-induced bubble dynamics and material damage assessment 3) Developing AI and machine learning models for robot-assisted laser surgery and
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. The appointment is viewed as preparatory for a full time academic or research career. The appointment is not part of a clinical research training program, unless research training under the supervision of a senior
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or scholarship, and may include teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless
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Physics, Astronomy, Astrophysics, Computer Science or a related field by the start date ● Strong background in observational or computational cosmology, large-scale structure, weak lensing or image