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on developing machine-learning surrogates for electronic structure and electrostatic potential and using these models to predict structural and electronic evolution under applied bias. Methods may include density
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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to study chemical transformations in materials. 2. Artificial Intelligence Applications: - Leveraging conventional machine learning techniques for materials property prediction and Bayesian approaches
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performing experiments to acquire data, using and maintaining research equipment and instruments, compiling, evaluating and reporting test results. Knowledge and experience in chemical thermodynamics, kinetics
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to the Lab’s broader effort in CH4 and CO2 utilization R&D. The role will require the individual to work with personnel that perform machine learning and molecular simulations and electrochemical device testing
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reinforcement learning Experience with high-performance computing, physics-based simulations, and multimodal data workflows Demonstrated ability to train and deploy AI/ML models using simulated and experimental
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; experience with machine learning is a plus Demonstrated record of peer-reviewed publications Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Qualifications
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or equivalent in the scientific application of this knowledge and practical laboratory experience. Skill in devising and performing experiments to acquire identified data, using and maintaining research equipment
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. The position will require flexibility and a willingness to learn new techniques and approaches. In addition, there may be overnight experiments being run unattended, the candidate must be able to respond
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campus in Lemont, Illinois five days per week. Preferred Qualifications Proficiency in programming (e.g., Python) for advanced data analysis, machine learning, and computer vision to accelerate insights