79 cyber-security-machine-learning Postdoctoral positions at Oak Ridge National Laboratory
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seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making
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integrating human-in-the-loop reinforcement learning approaches. Responsible AI: Exploration of privacy-preserving AI techniques, enhancing AI safety, and addressing vulnerabilities and defenses in Large
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. in Quantum computing, Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a closely related discipline, with demonstrated knowledge of or research experience in
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choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral
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: Experience applying machine learning methods for predictive analysis. Expereince with the Python programming language. Experience with the creation, validation, and use of synthetic data for constructing
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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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scientific journals in a timely manner. Maintain accurate and thorough experimental records and ensure compliance with environment, safety, health, and quality program requirements. Deliver ORNL’s mission by
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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that combines mechanistic ecophysiology with AI, such as: Physics-informed machine learning and neutral networks to investigate plant physiological / abiotic relationships Bayesian statistics and neural and