33 modelling-complexity-geocomputation Postdoctoral positions at Oak Ridge National Laboratory
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computing AI on High-Performance Computing (HPC) cluster. Examples on areas of research interest include but are not limited to: Vision transformers. AI foundation models. Computing and energy-efficient
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scientific datasets. Major Duties/Responsibilities: Designing and developing foundational AI-driven techniques for the generation and exploration of complex, large-scale scientific data. Publishing research in
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-driven techniques for uncertainty quantification and visualization of complex, large-scale 2D/3D scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and
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-driven techniques for the generation and exploration of complex, large-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel
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maturation, characterizing performance and properties of nuclear fuels and materials, and generate the data to advance physical modeling and simulation. The primary function of this open position is to perform
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Plant Phenotyping Laboratory (https://www.ornl.gov/appl ). Perform phenotypic characterizations of transgenic and genome-edited lines in poplar and other model or bioenergy plants Perform molecular and
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or machine learning potentials (iv) modeling of the solid and aqueous interfaces. Research proposal or concept writing experience. Programming experience for workflow development and scientific computing
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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
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Qualifications: Ideal candidates will possess a background in nuclear engineering. Previous experience using thermal hydraulics models and codes Previous experience using the MOOSE framework. Familiarity with
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Substantial programming skills using Python or modern C/C++ Experience with machine learning and deep learning libraries Experience building AI models in platforms such as TensorFlow, Keras, or PyTorch