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Field
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, genomic datasets, machine learning, and experimental methods to investigate how the tumor microenvironment and gene regulatory factors control tumor metastasis cascade. By advancing our understanding
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, and machine learning, the program prepares graduates to drive progress in fields like renewable energy, 5G, cyber-physical systems, and smart infrastructure. University Information The University
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, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race
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status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment
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interpreting wet-lab synthesis data are encouraged to apply and will have opportunities to explore machine learning-guided approaches in chemistry. In addition to excellent research skills, we are seeking
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly skilled workforce
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27710, United States of America [map ] Subject Areas: Statistics / Statistics Biostatistics / Biostatistics and Data Science Data Science / Machine Learning Appl Deadline: none (posted 2025/02/12
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Education and Experience Preferred experiences include research in cognitive neuroscience, human functional brain imaging, psychology, neurology, psychiatry, machine learning, data visualization, and data
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include, but are not limited to, using the latest computational learning-driven approaches, including computational social science, foundation models and multimodal machine learning, to enhance
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. Mathematical techniques include qualitative and numerical analysis of deterministic and stochastic dynamical systems, optimal control, network models, and machine learning. Preference will be given to candidates