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in high-impact venues Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of High Energy Physics or Nuclear Physics, or a closely related discipline
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have expertise in? What is your experience with software development? What is your experience with collaborative projects with experimental groups? Position Requirements Recent or soon-to-be-completed
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to contribute to other large-team scientific projects in materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Required skills: Recently completed PhD (within the last
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for this postdoctoral position to work on development and scaling of the data infrastructure and software for AI applications on supercomputing systems and AI testbed systems. The postdoc will work on multimodal data
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, electrical engineering, materials science, or a related field at the PhD level with zero to five years of employment experience. Hands-on experience in one or more of the following: Cryogenic detectors (TES
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evening/weekend hours. Position Requirements PhD (completed within the last five years, or soon to be completed) in Physics, Chemistry, Materials Science, or a related field. Background in ultrafast science
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Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of physics—ideally in accelerator science or engineering—or a closely related field Demonstrated experience or strong interest
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collaborating with a software engineering team to translate research into production-ready tools. The successful candidate will be part of an inter-lab, highly inter-disciplinary team of experts in ML, applied
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manuscript to be submitted). Position Requirements This level of knowledge is typically achieved through a formal education in electrical engineering, mechanical engineering, physics, or a related field at the
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position to work on development and scaling of the data infrastructure and software for AI applications on supercomputing systems and AI testbed systems. The postdoc will work on multimodal data management