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for coarse-mode aerosol and cloud data (e.g., image processing, machine learning) You will advance and maintain the University of Vienna Core Facility (CF) “ACTRIS Aerosol Observatory” instrumentation, and
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processing and statistical data analysis. Familiarity with flow modelling techniques (CFD) or machine learning for fluid flows. Aptitude for team work and excellent communication skills in spoken and written
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an excellent opportunity for a postdoctoral researcher interested in experimental nuclear physics, machine learning, and detector development. The successful candidate will contribute to the Iowa State
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scattering and direct dark matter detection, using advanced cryogenic detectors. The MBI hosts a research group dedicated to Machine Learning in Particle Physics. Qualifications: PhD in Particle Physics
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31 Jul 2026 Job Information Organisation/Company Computer Vision Center Research Field Computer science » Other Researcher Profile Established Researcher (R3) Positions Postdoc Positions Application
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to density functional theory (DFT) calculations and the generation of high-quality atomistic datasets for the development of analytical bond-order potentials (ADP) and machine-learned interatomic potentials
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, or machine learning) Experience working with various animal models Ability to work in an interdisciplinary research environment Specific Requirements Programming experience (Python and R) Experience with
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position within a Research Infrastructure? No Offer Description Activities and context: The fellow will develop machine-learning interatomic potentials (MLPs), trained on density functional theory-DFT data
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of work: We combine a unique methodology of recording the activity of single neurons in humans with advanced analytical approaches, such as machine learning and multidimensional analyses, to better
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events for postdocs. UNLV currently employs postdoctoral scholars across a wide range of disciplines. Learn more about UNLV's postdoctoral scholars. MINIMUM QUALIFICATIONS This position requires a