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Field
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on the development and analysis of continuous and discrete models in connection with convex and nonconvex optimization problems and monotone inclusion systems. Our ideal candidate already has experience with modern
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research potential. Candidates will be considered with background in the areas of hyperbolic PDEs and optimization problems. Expertise in numerical simulations (with Matlab or Python) will be valued
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devices using broadband spectroscopy and electron microscopy The position offers a stimulating interdisciplinary environment and opportunities to develop advanced skills in numerical optimization
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date). Strong background in power systems analysis (OPF, state estimation) and numerical optimization/control. Proficiency with Python/MATLAB and power-system toolchains (e.g., MATPOWER/OpenDSS
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today. Their convergence has the potential to redefine how we simulate, optimize, and understand complex physical systems. Integrating AI into quantum computers and simulators can help overcome current
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devices using broadband spectroscopy and electron microscopy The position offers a stimulating interdisciplinary environment and opportunities to develop advanced skills in numerical optimization
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Mathematics, or a closely related field. Design and optimize multimodal LLMs to encode, fuse, and reason over heterogeneous scientific data from diverse modalities such as numerical tables, text, and images
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developing machine learning surrogates and emulators for dynamical systems. Proficiency in managing large datasets and training with GPU-enabled computing resources. Expertise in numerical optimization and
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Integration of microglia into assembloid systems and optimization of co-culture conditions Phenotypic characterization of disease-relevant features, including neuronal loss, microglial activation and astroglial
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the interaction between wind farms and the atmospheric boundary layer using a combination of wind-tunnel experiments, field measurements, and advanced numerical simulations. The ultimate goal is to gain fundamental