77 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-";" 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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(e.g. weather, hydrology). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative
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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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If your Ph.D. has already been awarded, a copy of your Ph.D. diploma Candidates selected for interviews will be asked to provide the names and contact information for three references Start Date We
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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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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
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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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-material production, and recycling; compile life-cycle inventories from scientific literature, technical reports, patents, public industrial information, supplier data, and other sources; translate chemical