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resources and collaborating across ORNL, federal agencies, and academic partners. Key Responsibilities: Develop and apply scalable molecular dynamics (MD) and multiscale simulation workflows for biomolecular
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involving optical imaging, ultrasound systems, and/or contrast agents Develop computational models and reconstruction algorithms for imaging systems Analyze experimental data and prepare manuscripts
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routine background checks. Essential Duties and Responsibilities Neuroimaging data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms
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interdisciplinary, and together we contribute to science and society. Successful candidates will join the Computational Biology group, led by Prof. Antonio del Sol, which develops computational models to address
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, curate, and analyze field measurement datasets and associated environmental and economic information for model parameterization and validation. Develop or enhance model algorithms simulating carbon and
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, and unmodeled dynamics remains a key challenge. This position focuses on developing and validating methods that jointly address safety, performance, and reliability of learning-based control and
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be on creating and optimizing state
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of teaching and learning. Successful candidate will bridge the fields of AI development and education research, working closely with other AI researchers in M3S to contribute in both the creation of generative
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by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational