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physics who are motivated to work across disciplinary boundaries and develop new experimental capabilities. Major Duties/Responsibilities: Design and conduct experiments combining nanoscale photonics
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/Responsibilities: Design and implement a modular ROS 2 software architecture for onboard sensing, autonomy, mapping, data logging, launch management, and configuration management. Develop and integrate ROS 2 drivers
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. This position resides in the Multiscale Modeling and Materials by Design (M2MD) Group within the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral
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Preferred Qualifications: We are interested in candidates with general research experiences in quantum optics and quantum information science. Priority is given to candidates with experience on the design
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of analytics into production systems Knowledge of experimental design, uncertainty quantification, scientific machine learning, or digital twin methodologies Experience collaborating across national laboratories
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. The position will allow significant interactions with researchers of varying backgrounds and other opportunities for professional development. This position lives in the Alloy Behavior and Design Group in
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characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Design and evaluation of approaches for time-sensitive or data-intensive processing of data originating
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, reinforcement learning, monte-carlo tree-search, causal ML etc. Design, develop, and validate interpretable cross-modal AI/ML models incorporating features from electronic structure theory for predictive
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, including: Surrogate models or learned potentials Generative models for biomolecular design Representation learning for biomolecular systems Familiarity with protein–protein interaction (PPI) networks