336 machine-learning-"https:"-"https:"-"https:"-"UCL"-"UCL" Fellowship positions in United States
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Field
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, machine learning and AI-based computational tools to advance biomedical as well as oncology research. The fellow will work under the supervision of Dr. Veera Baladandayuthapani and there will be
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, and AI/machine learning would be helpful for the role. Experience with participant recruitment and retention as well as clinical human subject studies is a plus. Special Instructions Application
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Raman imaging technologies for safety and quality evaluation of agricultural products. Learn artificial intelligence/machine learning methods to evaluate hyperspectral image data to assess safety and
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Fellow will help mentor undergraduate students, work with Center for Health Research staff and will have the opportunity to teach classes by separate assignment as a part-time lecturer. This position will
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, Geography, Civil Engineering, Computer Science, Mathematics, Physics or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning
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the devastating disease avian coccidiosis. The secondary goal is to compare various Eimeria spp. to identify genes involved in intestinal cell specificity, virulence, and markers of drug resistance. Learning
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control, numerical analysis and scientific computing risk-averse and fractional models, digital twins and data-assimilating models, machine learning and neural networks (including operator learning and
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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to the continent, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including artificial intelligence (AI) and machine learning, to help
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such as: Causal inference and the design and analysis of experiments Reinforcement learning and sequential decision-making Analysis of complex systems, networks, and large-scale data Machine learning