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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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electron beams, advanced beam-manipulation for precise electron-beam shaping, and ML for accelerator science. Responsibilities Develop and deploy ML algorithms for autonomous operations and optimization
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analysis across time and conditions Algorithm design and modeling. The role offers significant intellectual freedom and opportunities to shape the direction of the research. Minimum Qualifications: • PhD in
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and resilience across heterogeneous computational resources while addressing workflow requirements for scientific applications. Validate distributed intelligence algorithms at scale on ORNL's
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grid planning. Design and code efficient algorithms for large-scale optimization problems using the Julia programming language and packages such as JuMP.jl. Experience with Xpress and Gurobi are a plus
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High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). Biomass burning is an important source of aerosols and trace gases to the atmosphere and is a major
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giving academic presentations. *Trained as a theorist in either condensed matter (CM), atomic, molecular and optical (AMO) physics or in quantum information theory. *Interested in quantum algorithm and
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testing of model-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs
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to algorithms, and cross-platform co-design across superconducting, neutral atom, and diamond-based systems, guided by quantitative resource estimates targeting DOE-priority scientific applications. Position