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completed within the last 5 years or expected to be completed soon. Expertise in AI/ML methods in an environmental or Earth science context Experience programming in Python or related languages A strong
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common scientific programming languages such as C++, Python, and/or Julia and version control systems. Experience in parallel programming with one or more common parallel programming models, like MPI
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret
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interact closely with industry partners. These engagements will play a vital role in ensuring success of programs and the adoption by project sponsors, and in developing your network across academia and
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quality program requirements Maintain strong commitment to the implementation and perpetuation of values and ethics Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core
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material, device, and process scales Plan and execute experiments to support and augment modeling efforts Conduct simulations using state-of-the-art tools to supplement model development Contribute
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in programming and simulation tools such as Python, MATLAB/Simulink, and/or ML frameworks (TensorFlow, PyTorch) Experience with physics-based modeling Strong analytical and problem-solving skills, with
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represent the organization by giving technical presentations to DOE program managers and in large public forums. Basic Qualifications: A PhD or equivalent experience in nuclear, mechanical, or chemical
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with quantum and classical programming languages and scientific computing. Preferred Qualifications: We welcome candidates with strengths in several of the following areas; no single candidate is
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conferences. Supporting collective team goals, working harmoniously with colleagues, and maintaining rigorous compliance with environment, safety, health, and quality program requirements are fundamental