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) Lattice QCD at the Intelligence Frontier (Phase II), and 2) AI-Enabled Optimization of Quantum Circuit Design for Realistic Nuclear Problems (Phase I); and two Topical Collaborations: 1) 3D quark-gluon
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-driven modeling, analysis, and optimization for diverse space systems and applications. Qualification requirements Appointment as postdoc requires academic qualifications at PhD level. How to apply Your
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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developing learning-based perceptive approaches. You will develop learning and/or optimization based approaches to multi-robot path and motion planning and coordination, integrating multi-modal perception and
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well as to the geometric optimization of the separator, including the swirl generator. Mandatory requirements PhD in mechanical, naval or aerospace engineering, or a related field. Proven experience in numerical simulation
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postdoctoral position focused on the development of a novel vertex detector concept for FCC-ee. The successful candidate will contribute to detector prototype testing, detector simulation and optimization, and
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-Lab in Neuchâtel, within an international and multidisciplinary research environment with strong links to the photovoltaic industry. Main duties and responsibilities You will develop and optimize PV
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constitutive parameters from a single informative test through Bayesian optimization, together with quantification of measurement and model-form uncertainty. Approximately half of the effort will extend
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. The College offers MS and PhD degrees in optics and photonics, and a BS degree in photonic science and engineering. The faculty engages in fundamental and applied research and education in lasers
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for applications. The ideal candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems