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enable the development of PE-based pipes with a longer service life for use in the mining sector. Work plan: The work plan aims at the development of new PE-based pipes with high abrasion resistance. It
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are integrated from long-term research to short-term applications in linkage with incubation and start-up ecosystems. About GSMI: Geology and Sustainable Mining Institute (GSMI) is based on a new strategic vision
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and Applications, R Language for Statistics, Data Mining with Big Data, Artificial Intelligence and Deep Learning, Statistical Reasoning for Business Decisions, Data Visualization; Highly Desired: Text
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with specializations in data science and actuarial science. More information about the department is available at https://www.sdsmt.edu/academics/academic-departments/mathematics/ . South Dakota Mines is
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activities as a priority on the following topics: - " A research proposal using data mining, Artificial Intelligence or model reduction or digital twins that matches the key topics of section n°11
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Colorado School of Mines, Department of Physics Position ID: Colorado School of Mines-Department of Physics-TTFPEQP [#31030] Position Title: Position Location: Golden, Colorado 80401
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that you will help us to build the sustainable companies and societies of the future. We are one of the leading universities in Europe in mining technology and metallurgy. The university conducts research
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coal mining heritage, with hundreds of abandoned and flooded mine seams. Current groundwater levels are the highest ever recorded, and are rising due to the cessation of mine water pumping and climate
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build the sustainable companies and societies of the future. We are one of the leading universities in Europe in mining technology and metallurgy. The university conducts research along the entire mining
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 10 hours ago
] Makhlouf, Karima, et al. "On the impact of multi-dimensional local differential privacy on fairness." Data Mining and Knowledge Discovery 38.4 (2024): 2252-2275. - [5] Bagdasaryan, Eugene, Omid Poursaeed