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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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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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. The Department of Cell Biology is looking for a postdoc candidate to conduct research on tissue morphogenesis using zebrafish as a model system. The candidate will ideally have a training in
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learning and image processing techniques for estimating the onset of arterial disease. 2)Implementation of denoisers as priors for the solution of inverse problems. Implement code in PyTorch and other
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of Civil and Environmental Engineering / Chaney Lab: Perform the core of the proposed research activities including processing the remotely sensed LST to compute the spatial statistics, run the HydroBlocks
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Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer programming, preferably python, and will ideally have experience in working with
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and dynamic wave propagation, in particular: (i) developing domain decomposition methods, (ii) damage models, (iii) nonlinear mechanics. 2) Validate the model by performing simulations using
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all applicable University and departmental policies and procedures. The postdoc candidate is expected to: 1) Develop coarse-grained or mesoscopic models of dynamic DNA nanostructures and polymer-grafted
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data, identifying structural errors in the dataset, and for maintaining a record of all steps from data extraction to dataset assembly · Fitting of machine learning models · Development of instrumental
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childhood. The project integrates exposure modeling, biomonitoring, and immune profiling to assess early-life susceptibility and long-term health impacts. The Scholar will work closely with Dr. Kate Hoffman