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6 Sep 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Electric Energy Research Field Technology » Energy technology Technology
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at the IBDM (Institute of Developmental Biology of Marseille) within the “Physical approaches to cell dynamics and tissue morphogenesis (PoM)” team, and at IUSTI (University Institute of Industrial Thermal
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://stanfordsciencefellows.stanford.edu/apply(link is external) Stanford Energy Postdoctoral Fellowship: https://energypostdoc.stanford.edu/(link is external) Data Science Fellowship: https://datascience.stanford.edu/programs/data-science
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the Geophysics and Energy Geology Groups. Process geophysical datasets, with specific emphasis in MT, and generate 2D/3D inversion models. Create and manage large geologic and geophysical datasets in multiple
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
and environmental scientists. The candidate will teach undergraduate and graduate courses that support our EMES (https://emes.unc.edu/ ) and Environment, Ecology & Energy Program (https://e3p.unc.edu
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, immunology, neurobiology, and cell biology. The Duke Center for Advanced Genomic Technologies (https://cagt.pratt.duke.edu ), an initiative established by the Pratt School of Engineering and School of Medicine
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The University of Manchester has a strong history of research into offshore renewable energy, with leading international activity in wave hydrodynamics and computational engineering. We are here
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B-cell epitopes Combination immunotherapy with chemotherapy, targeted therapies, and immune checkpoint modulation Translation of peptide vaccines from preclinical models to Phase I clinical trials
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the challenges they face with energy, waste, and productivity to reduce carbon cost, improve resilience and drive economic growth. College / Directorate College of Engineering, Design & Physical Sciences Full
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laboratories for chemistry, materials, biology, etc. AI/ML for predictive modeling and inverse design Generative models, reinforcement learning, and agent-based approaches to streamline experimentation and