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Generative AI and Machine Learning skills. This position resides in the AI Operations Program office within the Application Development Division of the Information Technology Services Directorate. Our AI/ML
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-body ab-initio methods for description of electronic, magnetic, and vibrational properties in a range of materials Expertise with artificial intelligence and machine learning approaches will be also
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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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technical leadership in AI security evaluation mechanisms. Required Qualifications Master’s Degree in Computer Science, Computer Engineering, Cybersecurity, or related fields with 7-10 years of experience
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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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, 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
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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