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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 11 days ago
of hybrid modeling frameworks for electromobility, combining physical models, graph-based representations, and data-driven approaches. It aims at integrating large-scale mobility data to improve
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uses two Heavy Vehicle Simulators (HVS) to simulate traffic loading on pavement test sections. Using a combination of electric drive and hydraulics, the HVS can apply up to a 32,000 lb load for up
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or diagnostic testing; assist with collection maintenance & reporting of clinical research data. Minimum Education Required: Bachelor's Level Degree or equivalent combination of education and experience with a
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projects. Participate/assist in manuscript writing for publication in scientific journals and/or presentations. May also assist in grant writing. A combination of education and relevant experience from which
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Sciences, Health Sciences or medical field, or equivalent combination of education experience required. 0 years of relevant experience required. Desired Experience: Prior experience conducting human subjects
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to the research of the laboratory. EXPERIENCE: Prior experience in laboratory environment preferred. Consideration may be given for a unique combination of education and biology or chemistry experience, such as
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and initiatives Other Duties as assigned A Bachelor's degree or an equivalent combination of education and experience and at least 2 years of experience from which comparable knowledge and skills can be
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or medical field, or equivalent combination of education experience required. 0 years of relevant experience required. 2-4 years of relevant experience preferred. Create a Job Match for Similar Jobs Logo About
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on tumor ablation in combination with chemotherapy and immunotherapy. This NIH and DoD-funded project aims to elucidate the mechanisms by which ablation therapies influence the tumor microenvironment and
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postdoctoral research associate to work with Professor Michael Desai at Harvard University on projects involving inferring sequence-function landscapes, using a combination of empirical data and ML methods (e.g