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Center for Astrophysics | Harvard & Smithsonian | Cambridge, Massachusetts | United States | 2 days ago
world-class scientists, contribute to current and on-going research, and develop essential skills in data analysis, numerical modeling, and scientific communication. With personalized mentorship, access
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, and procedures related to campus safety. Go here to review: https://safety.temple.edu/reports-logs/annual-security-report You may request a copy of the report by calling Temple Department of Public
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energy consumption. The demonstration of high-power energy recovery (exceeding 1 MW), particularly for high currents, remains a major challenge. It requires detailed simulations of beam dynamics o study
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topics such as statistics, high performance programming, machine learning and using data to constrain cosmological models. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs
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applications of computation, modeling & simulation, and data-driven discovery. Complementing its educational mission, CDS faculty develop, conduct, and disseminate cutting-edge, externally funded
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, graph neural networks, physics-informed ML) to approximate PF results Train models using simulation results generated from conventional power flow solvers Evaluate AI-based approximators in terms
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numerical models of rainfall–runoff and open-channel hydraulics in complex urban and rural settings to quantify flood depths, velocities, and risk; evaluating culvert/bridge performance and conveyance
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consultation model for patients with palliative care needs. Key Tasks and Responsibilities The successful candidate will be expected to: a) Refine the study protocol, prepare interview schedules, and manage the
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 2 months ago
interaction to liquid metal pool and microstructure generation. To this end, the main focus of the PhD project is the AI assisted multiphysics modeling/simulation of the LPBF process. The project aims
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the following is desired: - Agentic and sequential decision-making for autonomous experimentation, including active learning and optimal experimental design - Generative and probabilistic modeling