55 algorithm-development-"Multiple"-"Prof"-"Prof" Postdoctoral positions at Duke University
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new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks
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development of competitive research proposals. • Provide mentorship to graduate and undergraduate students in the lab. Required Qualifications • A Ph.D. in environmental economics, urban economics, public
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modeling are pluses. Other qualifications include a Ph.D. in Biology, Evolution, Ecology or allied fields and evidence of strong research productivity through publications and participation in conferences
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: Engineering / Biomedical Appl Deadline: none (posted 2025/06/16) Position Description: Apply Position Description Chory Lab Seeking Postdoctoral Associate (Automated Evolution postdoc) This postdoctoral
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University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations. 100
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and
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invites applications for a full-time Postdoctoral Scholar to join an interdisciplinary research team studying environmental exposures and immune system development in children. The Scholar will work closely
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policies pertaining to other schools at Duke University. The postdoc candidate is expected to: 1) Develop novel methods for incorporating scientific machine learning in solving problems in solid mechanics
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fellow will play a critical role in developing and scaling automated platforms for long-term mammalian cell culture, including systems for stem cell maintenance and differentiation. These efforts
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chemoproteomics experiments. The postdoctoral associate will be responsible for developing and optimizing custom data analysis and visualization pipelines; and should be prepared to integrate internal experimental