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? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0272.pdf CALL FOR APPLICATIONS: RESEARCHER Job/position/grant: Job reference: AE2026-0272 (CPES-Geral-CPES
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members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience in sampling algorithms and related areas
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of the CEFE in community ecology and species distribution models with that of IMAG in probability, statistical learning, and model validation. This project falls within the scope of statistical artificial
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systems. Specifically, the research will propose an integrated framework that will couple two core components: 1) advanced algorithms to optimise participation of HPPs, or more generally of VPPs integrating
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teaching scenarios both supported on an existing Hardware-in-the-Loop (HIL) equipment, enabling students to deploy their own control algorithms, state eObjectives By the end of the three-month period, the
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identification through lab-scale and field experiments. Key Responsibilities: Develop algorithms for guided-wave analysis, response analysis, sensor fusion, and system identification using distributed and multi
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 8 days ago
regions where ground radar and gauge networks are sparse. In the reverse direction, high-resolution precipitation fields (e.g., MRMS) provide spatially distributed validation for fine-scale soil moisture
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at the Jülich Supercomputing Centre (JSC) to run your algorithms/tools on large distributed computer systems. Write reports and research articles, as well as grant proposals, and regularly participate in
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Communication sciences Information science Engineering » Communication engineering Engineering » Electronic engineering Mathematics » Applied mathematics Mathematics » Probability theory Mathematics » Algorithms
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causal inference in heterogeneous data environments, addressing the challenge of enabling trustworthy causal analysis across distributed datasets while preserving privacy. The successful candidate will be