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-dimensional Bayesian inverse problems for image reconstruction and chemical reaction neural networks with sparsity-promoting (and edge-preserving) priors, including diffusion-based approaches. Neural solvers
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quantification. The specific project will be tailored to your expertise and interests; examples include: Efficient inference techniques for high-dimensional Bayesian inverse problems for image reconstruction and
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electrolytes, primarily solid-state, for applications in Li-based batteries. Polymer synthesis, electrolyte fabrication, construction and testing of prototype battery cells are all parts of the project
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