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turbulent combustion applications, as well as parallel scientific computing. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and
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with computer-aided design software. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and analysis of large datasets, and
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without constant direction in the performance of routine tasks. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Considerable: Experience in optical spectroscopy
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management through status updates, technical research reports, project presentations, and other regular channels. Develop technical ideas and proposals to advance the understanding of molten salt
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supervisors, peers, and Laboratory management through status updates, technical research reports, project presentations, and other regular channels. Position Requirements Knowledge of general principles
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-micron resolution of entire organs demands optimized data pipelines and methods to handle and visualize the resulting datasets. Additionally, beamline hardware must be optimized to ensure the highest data
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communication interfaces between Opal-RT, edge computing devices, OEM inverter using protocols like UDP, CAN, DNP3 etc. Aid with project management activities for DOE projects and developing safe operating
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The Scientific Software Engineering & Data Management Group in the X-Ray Science Division (XSD) at the Advanced Photon Source (APS) (https://www.aps.anl.gov/) invites applicants for a postdoctoral
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performs world-leading research in nuclear structure, nuclear astrophysics, fundamental symmetries, and nuclear data. The Group also manages and operates world-class detector systems as part of the ATLAS
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with fuel and chemical production technologies from U.S. Energy Information Administration (EIA) database, U.S. Environmental Protection Agency database (e.g. GHGRP, NEI), field data, process simulations