47 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" positions at Argonne
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operations is preferred, working knowledge of machine learning and artificial intelligence methods is highly desirable The successful candidate will demonstrate expertise in accelerator physics, accelerator
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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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, including both the large-scale production machines and the testbed machines featuring novel architectures such as Cerebras and SambaNova. The list below provides examples of the potential tasks
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science, including electronic structure methods molecular dynamics, and scientific machine learning. Experience with High-Performance Computing (HPC) systems and intelligent workflows. Demonstrated
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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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Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, Bioinformatics, or a related field. Strong programming skills in Python, with experience in AI/ML frameworks (PyTorch, JAX, Hugging
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computer-aided design software. Collaborative skills, including the ability to work well with other divisions, laboratories, and universities. Ability to demonstrate strong written and oral
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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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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
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collaboration with team members. Skilled written and verbal communicator, including the ability to present complex information so that it is understandable to a broad audience. Computer skills relevant for data