93 cloud-computing-phd Postdoctoral positions at Conservatorio di Musica "Santa Cecilia"
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Affairs. The FY25 minimum is $76,383. Our postdoctoral research fellowship program is dedicated to preparing scholars for an academic career in the domains of pediatric perioperative, pain, sleep, and/or
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opportunity to work on computational research related to one (or more) of the following areas: coastal dynamics (surf-zone to shelf), submesoscale processes, kelp-current interactions, or marine carbon dioxide
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common equipment, and also have the benefit of access to research facilities at Stanford University including core computing, microscopy, library, biostores, and analytical facilities. The Spin lab has
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on manuscripts, presentations, and research proposals Required Qualifications: PhD in psychology, neuroscience, biostatistics, computer science, or a related field. Strong interpersonal and technical skills
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postdoctoral fellow with interest in organic chemistry and radiopharmaceutical development. Successful candidates will join the Molecular Imaging Program at Stanford within the Department of Radiology, Stanford
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their own research program, under supervision of the principal investigator, as well as work across the many outstanding resources, institutes (e.g. Institute for Human-Centered AI) , and faculty labs across
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competitive funding if interested. Maintain meticulous research records and support operational/reporting responsibilities associated with clinical research. Required Qualifications: A PhD in computational
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publications. Preferred qualifications • Expertise in remote sensing applications to aquatic biogeochemistry, ocean color, or optical water quality. • Proficiency with cloud computing and high-performance
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external) Candidates from a diverse background are encouraged to apply. The applicant may hold a PhD either in physical sciences/engineering with a strong interest in translational research and motivation
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. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods