70 assistant-professor-computer-science Postdoctoral research jobs at Duke University
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genomics, metabolomics, or microbiome analysis Computer science, particularly machine learning, artificial intelligence, data science, or computational biology Mathematics or statistics, with experience in
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. The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the primary purpose of the appointment. The Postdoctoral Appointee functions under
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Duke University, Office of the Dean, Pratt School of Engineering Position ID: Duke -FacultyResearchMento -POSTDOCSALAHSHOOR [#30318] Position Title: Position Type: Postdoctoral Position Location
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. • Collaborate with mathematical modelers and experimentalists in the NIH Center to iteratively refine learned models. Qualifications: • Ph.D. in applied mathematics, computational science, statistics, machine
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Duke University, Biology Position ID: Duke-Biology-PD_DK [#30619] Position Title: Position Type: Postdoctoral Position Location: Durham, North Carolina 27708, United States of America [map
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, United States of America [map ] Subject Areas: Chemistry / Bioinformatics , Chemical biology , Computational Appl Deadline: 2025/09/15 11:59PM ** Position Description: Apply Position Description Job Opening: Postdoctoral
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techniques. · Compile and document results, maintain lab notes, and assist in writing reports and research manuscripts. · Assist in the development of new research procedures and techniques. · Contact
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, United States of America [map ] Subject Areas: Computer Science Machine Learning Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Appl Deadline: none (posted 2025/08
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mentoring, if needed. Minimum Qualifications The candidate should have a Ph.D. in Engineering, Applied Mathematics, Computer Science, or a related area. Experience 0+ years of postgraduate experience. Skills
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collaboration with Dr. Suthana and interdisciplinary team members. · Apply advanced statistical and computational approaches to investigate neural dynamics underlying memory consolidation and navigation