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candidate in the areas of Artificial Intelligence (AI) for materials science, with an emphasis on structure-property-relationships, materials optimization, materials under extreme conditions, and generative
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with college expectations and personal career goals. Qualifications: MD, PhD, MD/PhD or equivalent required. Successful completion of a pediatric residency program. Focused training in Pulmonary
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Network. https://www.eu4greenfielddata.eu/ ***Double Degree PhD Scholarship in Computer Science Opportunity: "Optimization-simulation coupling for the GHG emission estimation based supervision and
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performance under realistic conditions Funding category: Autre financement public PHD title: Doctorat en Genie PHD Country: Canada Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre
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) developing and optimizing fMRI pulse sequences; 3) developing and applying computational methods and machine learning approaches to characterize individual differences in brain representations; 4) contributing
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] Subject Areas: mathematical modeling, statistics, machine learning, data-driven modeling, dynamical systems, optimization Appl Deadline: 2026/04/01 04:59 AM UnitedKingdomTime (posted 2026/02/19 05:00 AM
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Scheduled Hours 40 Position Summary We are seeking a motivated individual with a BS, MD, or MD/PhD and a background in neurology and/or neuroscience to join our research team in the Department
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mission of the Cancer Institute and college. The candidate is expected to advance research in the Center Institute and collaborate with other cancer center faculty members to ensure optimal translational
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Bajcsy, PhD Information Technology Laboratory (ITL) National Institute of Standards and Technologies (NIST) Phone: 301-975-2958 Email: peter.bajcsy@nist.gov URL: https://www.nist.gov/people/peter-bajcsy
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PostDoc/Senior Scientist - Process and Plant Design in the Field of Liquid Organic Hydrogen Carriers
of multiphase reactions Assessment of different process configurations and application scenarios, including techno-economic evaluation Investigation of process intensification opportunities through optimized