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(NSSD). In this role, you will conduct fundamental research into the integration of Bayesian methodologies with system dynamics modeling, advancing statistical methods and the open-source scientific
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for the multi-billion-dollar Second Target Station (STS) project. Oak Ridge National Laboratory (ORNL) is the largest US Department of Energy science and energy laboratory, conducting basic and applied research
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machine learning and Bayesian calibration methods to enable multi-scale, multi-physics model development. Complete simulation verification, model validation, uncertainty quantification, and documentation
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divisions at ORNL. Major Duties/Responsibilities: Work closely with members of NTI and CNMS to develop new AI models for discovering novel permanent magnets with targeted properties using advanced concepts
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modeling, sensitivity and robustness analysis, Bayesian inference, inverse problems, parameter estimation, or model validation. Experience or strong interest in scientific AI/ML, including surrogate or multi
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. Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other related definitions. Knowledge of federated learning SOTA algorithms. Knowledge of distributed
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Requisition Id 16795 Overview: We are seeking a Maintenance Engineer who will focus on supporting all phases of target maintenance at the Spallation Neutron Source. The Target Systems Maintenance
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Distinguished Staff Scientist (Cancer Biology and Radiopharmaceutical Therapy Development and Advanc
include: Mechanistic studies of tumor response to radiation and targeted therapeutics, including DNA damage response, cell-cycle regulation, signaling, resistance, and radiosensitization. Development and
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to provide support in the development of novel radioisotope production targets and enhanced tools for analysis. You will work with scientists, engineers, and technicians to develop thermal and fluid flow
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delivery to the target. These systems typically utilize PLC, VME, or MicroTCA hardware, integrated using the Experimental Physics and Industrial Control System (EPICS) framework. This position reports