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Argonne National Laboratory, a U.S. Department of Energy National Laboratory, has an opening for a Postdoctoral Appointee specialized in physics-informed machine learning at the Department
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position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
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the VMS team. Position Requirements PhD Degree in Mechanical/Electrical/Computer Engineering or Computer Science. Experience in development and experimentation of automated driving controls for cars and
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soon-to-be completed PhD (typically within the last 0-3 years) in mathematics or a related discipline (e.g. computer science, engineering). Experience in mathematical optimization, machine/deep learning
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for machine learning/AI model development development using Pytorch, Tesnor Flow or similar platforms. Utilization of high-performance computational platforms. Writing and modifying scientific code in Fortran/C
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application. In your cover letter, please describe your previous experience with materials microscopy simulation/analysis; describe your experience with machine learning/computer vision; describe your software
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position to develop and apply machine learning algorithms and approaches for x-ray science and instruments. These machine learning methods will be integrated into a shared platform that will lower
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The X-ray Imaging group (IMG) of the Advanced Photon Source (APS) is currently seeking a postdoc with expertise in machine learning (ML) and image processing to develop cutting edge processing
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of machine learning in electronic structure calculations and advanced sampling. The postdoctoral researcher will work within the groups of Professor Giulia Galli (https://galligroup.uchicago.edu/ ) and Dr
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, respect, integrity, and teamwork. Desired skills and qualifications: Expertise in computer science, supercomputing, machine learning, AI. Application materials required: Upon submitting your application