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Research Fellowship (PRF) for PhD CS Program Location Rio Grande Valley, Texas College College of Engineering and Computer Science Department College of Engineering and Computer Science / Computer Science
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Research Fellowship (PRF) for PhD MSE Program Location Rio Grande Valley, Texas College College of Engineering and Computer Science Department College of Engineering and Computer Science / Mechanical
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The Position We are seeking an independent and motivated researcher for a Postdoctoral Fellowship in Aviv Regev’s lab to apply develop edge algorithms for analysis of single cell genomics profiles
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include: Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines. Build reproducible research pipelines and maintain reliable
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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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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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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Postdoctoral Research Fellow to work on the design, development, and realization of future communications technologies. You will be part of the team and contribute to ongoing developments in theory, algorithms
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
is important to note that this position is contingent on T32 funding. Education and Experience: PhD in Computer Science, Bioinformatics, Computational Biology, or related discipline. Knowledge of
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and