20 coding-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "Dr" Postdoctoral positions at Oak Ridge National Laboratory
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
& Computation Section, Center for Nanophase Materials Sciences (CNMS), Physical Sciences Directorate (PSD) at ORNL and will be jointly supervised by Dr. P. Ganesh, Dr. Rama Vasudevan and Dr. Vitali Starchenko
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with potential for extension. For questions about this position, please contact Dr. Nicholas Evans at nhe@ornl.gov . Benefits at ORNL: We offer competitive pay and benefits programs to attract and retain
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assess responses of environmental systems at the environment-human interface and the consequences of alternative energy and environmental strategies. Please contact Dr. Scott Painter (paintersl@ornl.gov
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of advanced materials. Research efforts will include the application of density functional theory packages and in-house codes, and the development of supplemental numerical tools, to describe
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Computational/theoretical chemistry and/or physics, chemical engineering, materials or a closely related field completed within the last 5 years. Preferred Qualifications: Experience with coding, electronic
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standard (version control, unit testing, continuous integration, etc.). Experience in the development of large-scale physics simulation codes, including coupling of multiple codes, and an understanding
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scientific outputs that may include peer-reviewed publications in top-tier water journals, professional scientific code/software contributions, and high-quality datasets. Candidates must also be willing
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coding (Python) for building energy modeling and controls Preferred Qualifications: Expertise in modern optimal control techniques (e.g., AI based controls) High level of competence in coding and scripting
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those skills to a variety of problems, and the ability to determine and understand the broader context of his or her research. Preferred Qualifications: Proficiency in multiple modern coding languages is
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., code interpreters, simulation frameworks, databases, lab instruments) and evaluation for long-horizon tasks. Experience with RL and post-training (reward modeling, preference learning, offline/online RL