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for applications. The ideal candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems
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systems. In parallel, they will design and develop agentic AI and physics-aware AI models to accelerate discovery and deepen mechanistic insight in catalysis. This work will be carried out in close
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industry. The candidate is expected to design and conduct experiments, analyze data and explore mechanisms behind the experimental observations, directly mentor the research of PhD and undergraduate students
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Requirements Completed PhD within the last 0-5 years, or soon to be completed and 0+ years of professional experience Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork
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- Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry, materials science, physics, chemical engineering, or a closely related field, completed by the appointment
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research program at the interface of theory and experiment. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of physical chemistry, inorganic chemistry
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theories. The candidate will also be expected to apply these models to predict the engineering behavior of materials in service environments. Position Requirements Recent or soon-to-be-completed PhD
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control and measurement, superconducting circuits, nanofabrication, and low-temperature experiments is strongly preferred. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years
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Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry, materials science, chemical engineering, physics, or a related field. Solid foundation and essential
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running