458 algorithm-development-"Multiple"-"University-of-California,-Santa-Cruz" positions
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, you will: Lead the development and execution of multiple AI/ML projects related to multi-scale, multi-cellular immune system modeling. Develop, execute, and implement AI/ML infrastructure to simulate
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employers. About the Global Campuses The university campuses operate as a distributed global network. For example, new programs may be developed and established at one of the network campuses, enhanced
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research and administrative activities. This involves small scale project management, to co-ordinate multiple aspects of work to meet deadlines. Carry out original research, including adapting existing and
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scale and resolution. This ambitious project spans multiple institutes including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute, bringing
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a 3-year DOE-sponsored project that started in September 2024. The Postdoctoral Research Associate working on P1 will develop and test deep learning algorithms for model emulation and model parameter
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Head and Neck cancer patients. This person will be working with our multi-disciplinary cancer specialty clinics and tumor boards. This individual will be expected to develop algorithms around national
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for, and mitigating weather and hydrological extremes, as well as to develop effective decarbonization strategies. The possible role of AI ranges from predictive models of solar insolation and wind variables
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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leader in HIV clinical care, research and education and has grown to encompass a network of specialty clinics, multiple research and clinical trials, an infectious diseases/HIV education program, an
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
looking for a postdoctoral fellow interested in developing either machine learning algorithms for high-resolution histopathology imaging/spatial-profiling data in combination with other modalities (e.g