63 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UNIS" Postdoctoral positions at Duke University
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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. Conduct
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the dynamics of microbial communities in time and space. Ongoing projects address questions on bacterial responses to antibiotics, the implications of horizontal gene transfer in community dynamics and evolution
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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. Occ
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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. Duke
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questions that lie at the interface of organic chemistry and chemical biology. The candidate will develop new chemical methods and small-molecule based probes to advance understanding of important biological
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structure-based ligand design. We are dedicated to advancing scientific knowledge and developing novel solutions in chemical synthesis, chemical probe development, and drug discovery. We invite highly
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welcome to apply. • Candidates should have a developing track record of research output • Programming proficiency in python is essential • Commitment to open research, as appropriate to the discipline
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research topics include mathematical modeling of microtubule dynamics in neuronal cells, analysis and simulation of RNA transport and organization in developing cells, and parameter inference and
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-Residence for a one-year appointment in AY 2026-2027 (9 months beginning August 1, 2026 and ending June 1, 2027). The Humanist-in-Residence will participate in the seminar meetings while also developing a
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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