56 programming-"the"-"DAAD"-"UCL"-"U"-"IDAEA-CSIC" Postdoctoral positions at Oak Ridge National Laboratory
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Research Associate to develop and apply scalable artificial intelligence (AI) / deep learning (DL) methods to advance multi-scale coupled physics simulations in support of the missions and programs of the US
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resources. Present and report research results and publish scientific results in peer-reviewed journals in a timely manner. Ensure compliance program requirements for environmental, safety, health, and
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, safety, health, and quality program requirements. Uphold strong values and ethics in collaborative research. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values
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and visualization technologies, programming systems and environments, and system science and engineering. Major Duties/Responsibilities: The position requires collaboration within a multi-disciplinary
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, artificial intelligence and machine learning, data management, workflow systems, analysis and visualization technologies, programming systems and environments, and system science and engineering. Major Duties
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offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you
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data analytics using tools in programming languages such as Python, PyTorch, Pandas, Scikit Learn, etc., in applied problem-solving contexts. Understanding of machine learning algorithms (gradient
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with environment, safety, health and quality program requirements. Maintain strong dedication to the implementation and perpetuation of values and ethics. Deliver ORNL’s mission by aligning behaviors
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algorithm development and application. Familiarity with common scientific programming languages such as C++. Experience in parallel programming with one or more common parallel programming models, like MPI
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applications. You’ll help design, train, and evaluate AI systems that plan, reason, and take actions to accelerate scientific discovery across domains (materials, chemistry, climate, fusion, biology, and more