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Field
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, many existing methods lack robustness guarantees and can behave unpredictably when faced with model mismatch, uncertainty, or distribution shift. This project is motivated by the need for deployable
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principles that govern product distribution and catalytic performance. Close collaboration with theory will be central to guiding and rationalizing the experiments, while synchrotron-based techniques will
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of optical surfaces (reflector/lens) that convert a given source distribution, typically LED, into a desired target distribution. The surfaces are referred to as freeform since they do not have any symmetries
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constraints. Depending on background and interests, the work may involve robust detection under distribution shifts and unseen interference conditions, resilient federated/decentralized (collaborative) learning
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constraints. Depending on background and interests, the work may involve robust detection under distribution shifts and unseen interference conditions, resilient federated/decentralized (collaborative) learning
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has an anticipated start date of May 18, 2026. You will: Lead advanced research projects on electricity system planning, including for bulk power and distribution systems; energy resources and delivery
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Extrapolation and Low-Reference Regimes Analyze MLFF feature spaces to find out-of-distribution atomic environments Use chemical neighborhood representations to detect sparse or unseen cases Combine ML features
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of tomographic imaging techniques to capture oil/water distributions in a 3D geometry. In the second half, we will use these techniques to study the flow and stability of an emulsion through a constriction
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values the qualities that an even gender distribution brings to the department, and therefore we particularly encourage women to apply for the position. We look forward to your application!
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the qualities that an even gender distribution brings to the department, and therefore we particularly encourage women to apply for the position. We look forward to your application!