273 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UCL" positions in United States
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Field
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experience and plans lie at the forefront of areas such as quantum computing, quantum algorithms, quantum simulations, and quantum error correction. Predominant research activities of the selected candidate
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foundations and applications of large language models (LLMs) or the development of novel AI algorithms utilizing the latest technologies for applications in science and technology. The successful candidate will
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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, prediction, and decision support and automation. Additional duties include but are not limited to: Developing and refining algorithms and workflows for crop monitoring, modeling, prediction, and decision
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responsibilities. · Continue and build research and development programs into AI algorithms and technologies in mechanical ventilation (both own programs and participating in ongoing programs in the Division
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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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, 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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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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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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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