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Field
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machine learning for molecular and material design; quantum computing for bioinformatics; quantum approaches for safe and sustainable molecular design; and benchmarking quantum simulations of materials
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calculations Machine Learning/Deep Learning techniques. Education and Experience: A PhD in physics, astronomy, or a closely related field must be completed before the position begins. Additional information
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machine learning with a physics-based understanding of the growth process. Doping and processing of ultra-wide bandgap semiconductors present challenges, but it can enable electronic devices with
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and meteorological modeling. Experience running or maintaining operational/automated forecast systems. Experience applying machine learning methods to air quality or geophysical data (e.g., forecast
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place to study and work. Postdoctoral Research Fellow position within Physics-Informed Machine Learning for Offshore Wind At the Department of Mathematics , there is a vacancy for a postdoctoral research
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the European Union through the COMPETE 2030 Programme, of Portugal 2030, under the following conditions: Scientific Area: Machine Learning Admission requirements: Candidates who cumulatively meet the following two
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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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practice in one or more of the following areas: film, media, or live performance. Interdisciplinary expertise and teaching are desirable. We would like to recruit a postdoc whose work crosses the boundaries
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two
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platforms a plus Experience applying machine learning, artificial intelligence, and large language models to research a plus The anticipated start date is September 1, 2026. The postdoctoral position incoming