946 development-"https:"-"https:"-"https:"-"UCL" Postdoctoral positions in United States
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develop computational methods to interpret complex data. In addition to research responsibilities, the postdoctoral researcher will actively engage in group meetings, journal clubs, and departmental
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We are seeking a highly motivated Postdoctoral Appointee with a strong background in artificial intelligence and machine learning (AI/ML), with particular emphasis on the development and application
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for a recent KU law school graduate to augment their legal education by conducting significant legal and interdisciplinary research and to further develop his/her legal research skillset in preparation
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program at the interface of drug delivery, biomaterials, and cancer biology. The successful candidate will play a key role in developing next-generation therapeutic platforms, including lipid nanoparticles
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for the immunotherapeutic treatment of cancer. Additionally, they are developing new vaccine concepts to prevent infectious diseases and cancer. The Barber Laboratory also works in the field of viral oncolysis, specifically
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variety of scientific principles and theories. 4. Maintains substantial knowledge of state-of-the-art principles and theories. 5. Develops advanced analytical models and systems and provides solutions and
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/maintenance, the collective supervision of graduate and undergraduate students, and dedicated activities related to professional development. Responsibilities: Research: Conduct advanced research in
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basic and translational neuroscience and genetics research. Our laboratory focuses on understanding neural circuit development and function, inhibitory neurobiology, cerebellar neural circuits, and
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. Potential areas of research include: research; program development; statistical analyses related to all phases of preparation of scientific papers, presentations, and grant applications; staff professional
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather