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Field
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) methods for modeling and optimization of metallic materials and advanced manufacturing processes. Participate in the design of integrated, scalable numerical methods and uncertainty quantification. Follow
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
optimization. Participate in collaborative research projects and mentoring. Contribute to academic publications, reports and seminars The selected candidate will be part of the Foundations Cluster of CIDSAI and
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of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific
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) optimization theory, numerical analysis, and applied mathematics. Our Research Interests: The AI + Quantum Group focuses on the frontier of AI + Quantum—the deep integration of artificial intelligence with
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-predictive control and optimization strategies, run high-performance numerical experiments, analyze data, and communicate your findings through journal publications and conference presentations. The ideal
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-predictive control and optimization strategies, run high-performance numerical experiments, analyze data, and communicate your findings through journal publications and conference presentations. The ideal
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experimental PhDs and Canon Production Printing to enable data-driven ink optimization. Why Join? Work in the multidisciplinary Processing and Performance of Materials group Work at the forefront of sustainable
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to provide scalable, faster-than-real-time capable methods and tools that enable the energy-optimal, cost-efficient and safe design and operation of future energy systems. Your Job This postdoctoral position
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of energy materials Develop and optimize advanced X-ray optical concepts with emphasis on maximizing photon flux, transmission, stability, beam quality, and experimental flexibility Design next-generation
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network optimization for 6G/FutureG wireless networks especially on the Internet of Intelligent Things under the supervision of Dr. Lingjia Liu (https://lingjialiu.ece.vt.edu). Successful candidates will