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conceptual DFT (linear response function, Fukui functions) or QTAIM theory (delocalization index), and their validation on a set of compounds known from the literature - interfacing a MLIP (Machine-Learned
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postdoctoral fellowship, starting September 2026. We welcome applications from recent PhD graduates (PhD in hand between September 2021 and September 2026) working in all areas of the Humanities related
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics Department Bashashati Laboratory | School
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 month ago
USNH Employees should apply within Workday through the Jobs Hub app A postdoctoral research associate is required in the Engineering for Agri-Environment Lab (https://sites.usnh.edu/eaelab/), led
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Eligibility criteria Instrumental optics and imaging (microscopy, camera detection) for biology. Skills in coding and experiment control. Basics of machine learning and/or signal processing. Teamwork
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capable of understanding, learning, and acting in complex, dynamic settings. The lab’s work lies at the intersection of computer vision, multimodal learning, and robotics, advancing next-generation embodied
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that challenge prevailing assumptions, employ cutting-edge technologies, or integrate machine learning with neurobiological data are especially welcomed. Projects focusing primarily on animal models with
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. The training program is also committed to cultivating an atmosphere that is conducive to learning by providing clinical postdoctoral associates with an appropriate blend of support and challenge. Postdoctoral
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metropolitan research university that provides an accessible, quality education through flexible learning and unparalleled internship opportunities. At UA Little Rock, we prepare our more than 8,900 students
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-party research funding are expected. We are particularly interested in a candidate in any field of economics who leverages state-of-the-art machine learning and causal inference methods to innovative