93 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at Princeton University
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Princeton University, Program in Applied and Computational Mathematics Position ID: 639 -PDRA [#26786, PACM2026] Position Title: Position Type: Postdoctoral Position Location: Princeton, New Jersey
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: 276187783 Position: Postdoctoral Research Associate Description: Ecology and Evolutionary BiologyPostdoctoral Research AssociateThe Department of Ecology and Evolutionary Biology at Princeton University has a
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: 272540354 Position: Postdoctoral Research Associate Description: Ecology and Evolutionary Biology Postdoctoral Research Associate The Department of Ecology and Evolutionary Biology has postdoctoral
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advance regenerative medicine. For more information about the lab, please visit https://mesa-lab.org/ .Projects will utilize in vivo mouse models, transcriptomic techniques, and advanced intravital imaging
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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on developing new systems models to examine social and biological drivers of infection inequality. The overarching goal of this postdoctoral position is to advance the use of mathematical and statistical models
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model output available to a diverse audience. Candidates must have a PhD in computer science, environmental and physical sciences, or a closely related field. The following attributes are desirable: a
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of laminar/neuropixel probes and electrical microstimulation to study attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH
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, lipid vesicles, polymer physics, active materials, single molecule biophysics, biomaterials, materials chemistry, fluid mechanics, rheology, and computational modeling. Candidates should apply at https
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advance regenerative medicine. For more information about the lab, please visit https://mesa-lab.org/. Projects will utilize in vivo mouse models, transcriptomic techniques, and advanced intravital imaging