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. The selected candidate will develop computational models at the mesoscale and/or macroscale based on the principles of mass, momentum, and energy conservation to describe processes such as morphological change
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. The candidate will work closely with computational modeling collaborators to validate reactor designs and optimize operating parameters. The candidate will be expected to contribute to report preparation
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bench scale micro-computed tomography and ultrasonic sensing methods to evaluate the state of charge and state of health of iron- and lead-based electrodes. Your research will be complemented by studies
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and engineers across Argonne, including the Materials Engineering Research Facilities (MERF) and the Argonne MXene Innovations (AMI) program, while collaborating with industrial and academic partners
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computational scientists, economists, engineers, and other researchers to develop data-driven, decision-relevant analytical tools for complex industrial systems. Key Responsibilities: Develop, improve, and apply
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collaboration and innovation. Position Requirements This level of knowledge is typically achieved through a formal education in Statistics, Machine Learning, Computer Science, Logistics/Supply Chain, or a related
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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-completed Ph.D. within the last 0-5 years in Atmospheric Science, Meteorology, Climate Science, Applied Mathematics, Data Science, or a related field with strong quantitative and computational research
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models for microelectronics materials Curate, manage, and integrate heterogeneous datasets from experiments and simulations Collaborate closely with experimental teams to benchmark and refine computational