45 programming-"the"-"DAAD"-"IMPRS-ML"-"FEMTO-ST"-"UCL"-"U"-"https:"-"Fermilab" positions at Argonne
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Intelligence, Machine Learning, Quantum Information and Quantum Simulation. The successful candidate will be expected to lead an independent research program in particle theory to strengthen and complement
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symmetries, and nuclear data. LER also plays a critical role for the ATLAS National User Facility, where it provides support for ATLAS Users, conducts its own research program, and develops and operates
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The Group Leader (GL) for the Electron and X-ray Microscopy (EXM) Group at the Center for Nanoscale Materials (CNM) develops, leads, and executes world-class R&D programs in electron and X-ray
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the domains of environmental, water, and energy system analysis. Prepares reports, papers, and presentations for conferences, workshops, and technical journals. Supports program development including
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physics, etc. Proficiency in Python or other scientific programming languages. Programming skills in numerical methods for image processing and AI/ML methods for quality improvement are advantageous
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and program managers. Position Requirements Minimum Education / Experience Requirements: A Ph.D. in physics, applied physics, electrical engineering, or related field. Additional Requirements: Normal
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with applying unsupervised ML algorithms such as autoencoders, clustering, to time-series data is preferred Experience with the data from HEP experiments is strongly required Programming expertise in
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of multi-omic data Programming Proficiency: Strong knowledge of Python, C/C++, Julia, and other relevant programming languages Ability to model Argonne's core values of impact, safety, respect, integrity
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, MATLAB, or similar programming environments for instrument control and data analysis. Excellent written and oral communication skills. Demonstrated ability to work both independently and collaboratively in
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interfaces. Programming and HPC: Strong scripting and data analysis skills; experience with high-performance computing environments and job schedulers. Demonstrated ability to work in multidisciplinary teams