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, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
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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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, United States of America [map ] Subject Areas: Engineering / Computational Science and Engineering , Machine Learning , Quantum Science and Engineering Appl Deadline: (posted 2026/03/05 05:00 AM UnitedKingdomTime, listed
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care for patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
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-Phenomenology (hep-ph) , High Energy Physics , High Energy Theory , Machine Learning , Neutrino physics , Particle , Particle Physics , Particle Theory , QCD , Theoretical high energy physics , Theoretical High
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Position Information Posting Number F00741P Position Title Postdoctoral Research Associate Department Industrial Engineering Location Arlington Job Family Faculty Position Status Full-time Rank Non
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in the United States. Preferred methodological skills include statistical analysis of survey and other large-n data, qualitative interviews, and/or text analysis and machine learning skills
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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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. Experience working with a high-performance computing (HPC) environment. Familiarity with machine learning and advanced statistics. Experience with analysis of time series data from intracranial EEG (iEEG
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, making use of intelligent AI-driven control planes. The applicants should have a solid theoretical background on machine learning, optical networks and fibre sensing and be willing to engage in testbed