68 data-"https:"-"https:"-"https:"-"https:"-"https:" "IMT Atlantique" Postdoctoral positions at Argonne
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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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independently and collaboratively; and analyze, interpret, and report experimental data. Build and refine data-analysis, automation, and closed-loop decision-making workflows using Python and related tools
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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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data is a must. Applicants must have strong communication skills (written and oral) and have the ability to work within an integrated multidisciplinary scientific research group and with scientists from
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The Data Science Learning division is seeking a postdoctoral researcher to develop and apply artificial intelligence and computational biology methods to investigate the molecular and cellular
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. Experience using high-performance computing clusters for simulation and data analysis. Experience with accelerator modeling and simulation tools such as ELEGANT, GENESIS, WarpX, ImpactX, RF-Track, or related
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structure of hadrons: mass, spin, and tomography, and 2) Nuclear Theory for New Physics. Further information on our group and its research activities can be found at www.anl.gov/phy/theory . Interested
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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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to molecular systems. - Familiarity with scientific programming and data analysis using languages such as Python or Julia, and experience with Linux and high-performance computing environments. - Strong written
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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