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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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productivity, labor productivity, and GDP that are driven by either climate change or air quality changes. Work will include use of output from global climate models (CMIP-class models) as well as Integrated
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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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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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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
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methodological publications in high- quality, peer-reviewed journals. Qualifications: Candidate must have the following: a doctoral degree in statistics or biostatistics; solid training in statistical methods; and
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Activities: Research Topic: Bioengineered Human Tissue Model for Juvenile Dermatomyositis Job Description: Our lab is focused on using bioengineered human muscle systems (myobundles) to research rare pediatric
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model over the Contiguous United States, and evaluate model deficiencies and model improvements to improve the modeling of spatial heterogeneity of LST in land surface models. In Addition, Will Also
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control