428 machine-learning-"https:" "https:" "https:" Postdoctoral positions in United States
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Computing Applications group in CSD has an immediate opening for a Postdoctoral Research Associate to design, develop, and deploy machine-learning and high-performance computing workflows, algorithms, and
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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion
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for this position will work as a member of an interdisciplinary team led by Dr. Colin Xu on Department of Defense (DoD)-funded research project involving the use of statistical and machine learning methods
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states, charge density waves, superconductivity, and quantum magnetism - Kagome materials and superconducting hydrides - Machine learning interatomic potentials (MLIPs) and data-driven atomistic
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development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing for one or more of the following: (1) reconstruction
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, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing multiscale simulation methods for quantum mechanical
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participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing. UConn has a vibrant
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Associate as part of Cornell’s Active Learning Initiative (https://teaching.cornell.edu/active-learning-initiative-0) for the AYs 2026 – 2028. We invite applications from candidates with a specialization in
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salary scales (https://www.ucop.edu/academic-personnel-programs/compensation/2023-25-academic-salary-scales.html ) set the minimum pay determined by rank and/or step at appointment. See the following table
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, dynamical systems, statistical machine learning, and neural time-series data. The goal is to better understand principles and mechanisms underlying distributed brain network computations through the dual