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-driven research group working at the intersection of computational genomics, clinical artificial intelligence, and imaging genetics. This position offers an exciting opportunity to develop novel algorithms
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materials science applications and algorithms for OLCF supercomputers Develop and apply advanced, compute-intensive materials simulation methodologies to study the fundamental properties of molten salt
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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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basic and applied engineering research, workforce development and technology transition. Our collaborations with industry, academia and government provide cutting-edge solutions to global technical
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was created to advance research in the mathematical, algorithmic, and statistical foundations of data science and their application to other disciplines. In addition to providing support to core foundational
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, etc. - ML-augmented numerical method development. - High-performance computing (HPC). - Quantum algorithm design. - Error correction or error mitigation. City
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). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology
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. · Developing and implementing computationally intensive algorithms using high-performance computing (HPC) clusters. · Managing and analyzing multiple large-scale datasets, including UK Biobank (UKBB
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
, scientific computation, scientific software and algorithm development, and data analysis; demonstrated ability to conduct original, high-quality research in computational fluid dynamics and/or computational
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. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects