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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
, and medicine. Key Responsibilities Collaborate with researchers to design, develop, and refine large language and generative models. Develop novel algorithms for generative modeling tasks and optimize
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computational chemistry/molecular physics will support the research program of Dr. Dmitri Babikov: Dr. Dmitri Babikov // Chemistry // Marquette University. The project will focus on the development of a quantum
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advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms
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to work on Bioinformatics and Computational Biology in Cancer Genomics and Immunology. This position will be involved in the development and/or application of computational approaches to understand
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scientists and other scholars within his academic and research communities. We are seeking one or more applicants to develop forward modeling software and a characterization and calibration plan for a new
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the Integrated Building Deployment and Analysis Group in the BTSD, ESTD at Oak Ridge National Laboratory (ORNL). The IBDA group leads the development of innovative methods for residential and commercial whole
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learning algorithms in PyTorch. Expertise in object-oriented programming, and scripting languages. Parallel algorithm and software development using the message-passing interface (MPI), particularly as
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Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods of research, testing and data
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
: Technology Development Advisors: Ryan Rogalin Ryan.Rogalin@jpl.nasa.gov (818) 354-3426 Applications with citizens from Designated Countries will not be accepted at this time, unless they are Legal Permanent
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods