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than 1,800 employees and nearly 21,600 students. Under the research subject Process Metallurgy at the Department of Civil, Environmental and Natural Resources Engineering, we are looking for two Ph.D. students
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computing (HPC) and parallel processing to enable the analysis of massive datasets. Experience in advanced statistical inference (e.g., Bayesian statistics, spectral methods) for extracting robust patterns
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, bandwidth, and multi-condition operation. To design and fabricate reconfigurable metasurface prototypes that implement a global tuning mechanism, and to experimentally characterize their electromagnetic
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complies with the legal requirements for the formalization of the contract in accordance with the Spanish labor law. To be eligible, candidates must officially apply in parallel to: https://www.unimedizin
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of protein variants Demonstrated experience with pooled, massively parallel screening approaches coupled to next-generation sequencing Skills to independently establish assays in yeast as a host system You
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
University to support outstanding research. We will foster programs in the areas of basic, translational, mechanistic, and population research. Position Summary The Phanstiel lab at UNC (http://phanstiel
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research teams. Preferred Qualifications Experience with commercial and/or open-source GIS tools and technologies. Experience in parallel computing (e.g., MPI, Spark) and/or cloud computing (e.g., AWS
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27 Jan 2026 Job Information Organisation/Company University of Siegen Department Embedded Systems Research Field Computer science » Computer architecture Researcher Profile First Stage Researcher
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requiring initiative and judgment by applying knowledge and understanding of federal and state-level civil procedure to make informed decisions about data categorization. Aggregate and review court filings