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: Artificial intelligence applied to seismics, neural networks, machine learning, synthetic data generation, seismic inversion, geological CO2 storage. Abstract: This research project aims to develop a synthetic
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-equilibrium processes; Casimir physics , Non-equilibrium quantum physics , Physics-informed machine learning , Quantum chaos and thermalization , Quantum Computation , Quantum Computing , Quantum Condensed
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machine learning within the Department of Electrical and Computer Engineering. The Postdoctoral Fellow conducts independent and collaborative research, publishes findings in peer reviewed conferences and
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partners. The postdoctoral researcher will also contribute to teaching in areas such as Machine Learning, NLP, AI for Education, Explainable AI, and Python-based applied seminars, supporting course
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fluids, quantum spin liquids and exciton fluids. • Data Management, Analysis & Machine Learning Knowledge and experience in high volume image-array data acquisition and management, development of custom
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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together with Jendrik Seipp, Senior Associate Professor in Artificial Intelligence at LiU. The research projects for the advertised position will be in the areas of automated planning and machine learning
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-performance computing resources suitable for large-scale machine-learning and foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025
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https://pubs.acs.org/doi/full/10.1021/acssuschemeng.5c0419 The successful candidate will be able to: Work safely and independently in a laboratory setting Learn new techniques and protocols Plan and
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off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation-tools.php CBC Requirement