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Field
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algorithms and code, software, and research publications • Prepare results for publications, work with collaborators in writing publications, and, in some cases, take the lead in writing publications
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Supporting Actions: Clean, organize, and link large administrative datasets (e.g., Medicare claims, prescribing data, and corporate ownership data) from multiple sources. Develop and maintain reproducible data
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algorithms using Monte Carlo simulation and Bayesian inference to distinguish normal tritium losses from suspicious discrepancies during transport, and to develop statistical thresholds that balance detection
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, that will drive research and innovations at multiple levels - from developing scalable quantum processor technologies to solutions for the quantum-classical control and readout interface, and all the way
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safety-critical tasks, such as healthcare or automated vehicles, where trustworthy models are required. The existing literature for the OoD detection problem focuses on the development of confidence scores
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optimizing algorithms, supporting HPC- and data-intensive workflows, and contributing to the development and evaluation of emerging technologies in high-performance computing, data analytics, and
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to test and evaluate SONAR signal processing and automation algorithms developed both internally and externally (may include travel to test sites for specific test events). Implement research grade
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School. Responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical
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is involved in the DUNE project with a broad range of responsibilities in detector construction, modelling and software development. This PhD project will focus on the development of a methodology for
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also be involved in improving object reconstruction, such as developing advanced algorithms for tau lepton identification or jet substructure / particle-flow techniques to identify Higgs bosons decaying