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-throughput workflows for data acquisition and analysis Contribute to on-the-fly data processing and integration with computational tools Collaborate with multidisciplinary teams in nanofabrication
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techniques in interfacial science; and mathematical techniques and computer programming for data analysis. Considerable skill in working interactively and productively in a multidisciplinary environment Good
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and processing strategies aimed at achieving high performance, cost-effectiveness, and manufacturability. The selected candidate will leverage the capabilities of the Materials Engineering Research
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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The X-ray Imaging Group (IMG) of the Advanced Photon Source (APS) is seeking a postdoctoral researcher with expertise in computational science and image processing to develop innovative methods
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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source for EIC and the design of the ePIC Barrel Imaging Calorimeter. Argonne National Laboratory, situated near Chicago, is a prominent multidisciplinary science and engineering research center. We are
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engineering team to translate the models into production. The successful candidate will be part of a cross-lab, highly inter-disciplinary team of experts in ML, applied math, HPC, signal processing