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EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites | Darmstadt, Hessen | Germany | 6 days ago
. In the EUMETSAT matrix organisation, the Remote Sensing and Products (RSP) division of the Technical and Scientific Support (TSS) department provides science support to the development and operations
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for ground-penetrating radar (GPR) and electromagnetic (EM) will be developed. These algorithms will enable high-resolution, quantitative time-lapse soil property measurements using high-performance, parallel
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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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executing the experiments Developing relevant algorithms for experimental data post-processing Mentor and work closely with multiple Ph.D. and M.S. students as well as four principal investigators from
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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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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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distributed energy resources (DERs). Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging
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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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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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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