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Division (MSTD) at Oak Ridge National Laboratory (ORNL), and who will focus on ORNL's continued development of methods to quantify shear (yield) strength of monolithic ceramic materials as a function of
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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Requisition Id 16802 Overview: We are seeking a Postdoctoral Research Associate for the development and application of advanced multiphysics simulations, and machine learning (ML) methods relevant
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Science group addresses this mission through the development of quantum computational methods and software for diverse scientific applications. Major Duties/Responsibilities: Work with a team to move
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calibration, coordinate-frame management, timestamp synchronization, and data acquisition across heterogeneous devices. Develop and evaluate multi-sensor localization and state-estimation methods that fuse
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still providing robust privacy guarantees. Develop novel privacy-preservation methods that accommodate the diverse privacy requirements of a large number of clients. Develop novel mathematically rigorous
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Research Group (IARG) at Oak Ridge National Laboratory (ORNL). The successful candidate will develop and deploy optical spectroscopy-based analytical methods, automated sampling approaches, and integrated
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quantum magnetism and strongly correlated systems, as well as classical methods such as exact diagonalization, tensor networks or DMRG, and quantum Monte Carlo. Familiarity with inelastic neutron scattering
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research and development in the areas of gauge field generation, linear and eigen-solvers, or novel analysis methods. This position will reside in the Advanced Computing for Nuclear, Particle and
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Requisition Id 16760 Overview: We are seeking an Applied Data Scientist to perform development of novel and advanced AI/ML algorithms. This work will support a broad user base by applying AI methods