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employees in matters related to waste management and transportation programs. Benchmark and share lessons learned with other DOE/Battelle laboratories and relevant professional networks. Align behaviors and
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excellence. Provide timely notification, documentation, and reporting of incidents, equipment failures, environmental events, and operational occurrences. Promote continuous improvement, continuous learning
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computational thermodynamic (CALPHAD) software, such as Thermo-Calc, DICTRA, PANDAT, or FactSage. Proficiency in materials data analytics, including correlation analysis and machine learning techniques. Preferred
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priorities. Willingness and ability to learn new research areas and contribute effectively with initiative and enthusiasm. Excellent written and verbal communication skills, with a demonstrated record of
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. Preferred Qualifications Familiarity with techniques for AI-on-AI adversarial evaluation, including reinforcement learning-based adversarial testing setups. Expertise in designing systems that support red
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in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
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in urban-scale building energy modeling, software development (esp. Python), or Artificial Intelligence/Machine Learning (AI/ML) Strong ideation, writing, and communication skills for establishing
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
ML concepts and architectures and hands-on experience with open-source AI/ML packages (such as pytorch, scikit-learn, tensorflow, JAX etc.). Preferred Qualifications: Good grasp of concepts in solid
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, collaboration, inclusion and continuous learning. Stakeholder Engagement & Partnerships: Serve as the external interface for the center: liaise with sponsors (DOE, other federal agencies, industry, academia