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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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engineering, materials science and engineering, or computer science and engineering. The postdoctoral fellow is expected to actively work with more than one CQISE faculty member at OSU to strengthen
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, you will be asked to indicate, which of the areas listed on the page above are of interest to you. The list includes positions covering Operator Algebras, Machine Learning, Analytic Number Theory
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and interventional datasets in high dimensions. Our interdisciplinary approach integrates interpretable machine learning, statistics, algorithms, and single-cell multi-omics. Position Overview You will
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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STEAM education and dynamic campus experience. As New York State's premier public polytechnic, SUNY Poly fosters innovation and interdisciplinary learning across its four colleges--Arts & Sciences
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mission utilizing the expertise, resources, and capabilities available at your hosting facility. You will acquire experience and training in areas related to fusion energy and plasma science and technology
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, machine learning, Experience in human electrophysiological research is a plus, experience in intracranial human research large plus, Knowledge of cognitive system is a plus, knowledge of neuronal basis
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modeling are applied. To learn more about the lab: https://www.mdanderson.org/research/departments-labs-institutes/labs/xufeng-chen-laboratory.html The incoming fellow will receive training and conduct
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/10.1126/science.adm8203. 2. Keleş, M.F., Sapci, A.O.B., Brody, C., Palmer, I., Mehta, A., Ahmadi, S., Le, C., Tastan, Ö., Keleş, S., and Wu, M.N. (2025). FlyVISTA, an Integrated Machine Learning Platform