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details on our research and recent publications, see the Geometric Machine Learning Group’s website: https://weber.seas.harvard.edu/ . For questions, please email [email protected] Applications will
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and rigor to drive their own research in the broad and multi-disciplinary areas of artificial intelligence machine learning big data and data analytics software and security mobility and autonomy The
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MOF synthesis and characterization. Special consideration will be made to candidates with experience in automation or machine learning. The postdoc will join a group which is focused on pioneering
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, audited, and trusted. The appointed researcher will publish in top venues in artificial intelligence, machine learning, and operations research; contribute to open-source releases; and work closely
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-based rule-based checks with advanced machine learning architectures, specifically Long Short-Term Memory (LSTM) networks and Variational Autoencoders (VAEs). The researcher will use historical QC
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posts Starting date: 14.08.2026 Job description: Postdoctoral Researcher - Probabilistic Deep Learning for Urban Air Quality (AEON-UP) Referenzcode: 1056 Arbeitsort: Geesthacht Bewerbungsfrist: 03.09.2026
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build predictive models of immune responses. Develop advanced and innovative machine learning methodologies and analyze data. The postdoctoral researcher will join the groups of T. Mora and A. Walczak
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aircraft (Cloud Physics Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
Research Triangle, the United States, and even the world. Position Summary The postdoctoral researcher will conduct advanced research in artificial intelligence (AI) and machine learning, with a focus
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, machine learning, computer science, statistics, engineering, medicine, or a related field. Strong candidates may have experience with large-scale human datasets, machine learning, statistical genetics