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involve the design and implementation of efficient reconstruction algorithms, including iterative regularization, PDE-constrained optimization, shape and topological derivative methods, and neural-network
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optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically in AI-driven
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optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically in AI-driven
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printing (metals, concrete, and composites) computational mechanics and structural topology optimization vision-based structural health monitoring autonomous and drone-based infrastructure inspection and
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for the control, optimization, and coordination of complex dynamical systems. The work will emphasize applications to multi-agent systems, including robotics, autonomous systems, and distributed
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects and mentoring
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects and mentoring
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects and mentoring
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, quadrupolar nuclei, or two-dimensional NMR methods, is highly desirable. Experience with computational methods such as density functional theory calculations, geometry optimization, and prediction
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, quadrupolar nuclei, or two-dimensional NMR methods, is highly desirable. Experience with computational methods such as density functional theory calculations, geometry optimization, and prediction