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AI and physics‑based simulation for complex mechanical systems. We are now seeking a postdoctoral researcher for a project aiming at physics‑informed autonomous control of machines operating in rough
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resonance imaging data among other imaging modalities, machine learning methods for prediction, treatment effect estimation, and contribute to understanding brain biomarkers of Alzheimer’s disease and their
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject and have a strong record of publication in the relevant literature. Good knowledge of machine learning algorithms is essential, as
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Argonne’s core values of impact, safety, respect, integrity, and teamwork. Preferred Knowledge, Skills, and Experience Experience applying machine learning or AI techniques to scattering, imaging
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(HIMS), in close collaboration with industrial partner BOR-LYTE and Smart Industry testbeds. This position offers a unique opportunity to combine inorganic chemistry, spectroscopy, machine learning, and
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Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep learning, with experience in time series forecasting or related
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our OU community can reach their potential. We recognise that different people bring different perspectives, ideas, knowledge, and culture, and that this difference brings great strength. We strive
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-driven machine learning approaches, they will improve our understanding of nutrient flows in agricultural landscapes. The postdoc will contribute to the development of databases representing the current
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with cardiovascular or fetal imaging data. • Knowledge of machine learning model development, validation, and clinical translation. • Experience working with DICOM data, PACS systems, and 3D
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commensurate with abilities and experience Type of Position Other Position Time Status Full-Time Required Education PhD in Engineering Required Related Experience see Skills / Knowledge / Abilities Required