80 linked-data-"https:"-"https:"-"https:"-"https:"-"INSA-RENNES" positions at Argonne
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collaborative, multidisciplinary environment that brings together expertise in quantum information science, computer systems, networking, high-performance computing, and scientific applications. The scientist
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The ALCF has an opening for a postdoctoral position in AI-assisted scientific visualization and intelligent data exploration. The successful candidate will join the Visualization and Data Analytics
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Three letters of recommendation—refer to applicant instructions for guidance CV—uploaded through the application link Graduate transcripts—refer to applicant instructions for acceptable format Letters
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work with a multidisciplinary team to advance agentic AI tools for simulation, interpretation, data analysis, and scientific discovery. The appointment is expected to last two years and the contract is
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for Microelectronics” —a physics-informed AI framework that links composition, structure, and operating conditions to defect evolution and functional performance. The successful candidates will lead experimental
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Qualifications: Experience using the MOOSE simulation framework is highly desired. Experience fitting complicated physics-based models against test data, including machine learning and Bayesian optimization
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, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral, and interpersonal
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range for this position is $72,879.00-$121,465.00. Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors
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reaction behavior, taking detailed observations, gathering and analyzing data and contributing to technical reports, publications, presentations, and future proposals. Position Requirements Recent or soon-to
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with data analysis and technical documentation; and contributing to publications, reports, and sponsor deliverables. The successful candidate will work closely with staff researchers and technical teams