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method, NSGA-II algorithm, heuristics, and rolling horizon approach. Minimum education and/or experience required: PhD with specialization in industrial engineering, modeling, or similar disciplines
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the Norwegian educational system The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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) ● Dr. A. Proust (Mistras, France) Secondments (1 to 6 hosting months) Contact information ● tahar.kechadi@ucd.ie ● guillaume.charrier@inrae.fr How to apply https://www.eu4greenfielddata.eu/phd-positions
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, quantum compilation techniques, and noise-aware algorithms for Rydberg architectures. Apply quantum optimization to real-world problems such as logistics, scheduling, and portfolio allocation, comparing
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use of data and algorithms. Excellent written and verbal communication skills and ability to communicate effectively with a variety of different stakeholders, e.g., academics, business executives
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, memory, timing, and cost are of main interest. The group members have expertise in a wide range of domains covering both hardware and software, including compilers, operating systems and algorithms
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, and inline interpretation. The work includes validating algorithms on a lab-scale sorting setup and linking spectroscopic outputs to recyclability scoring and Digital Product Passport data flows. Your
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are as important as high accuracy. Supervise student projects at BSc, MSc, and PhD level. Work with experts at the Jülich Supercomputing Centre (JSC) to run your algorithms/tools on large distributed
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subject area or subject specialism. A4 Conversant in Python programming and deep learning algorithms for image analysis. For appointment at Grade 7: A5 Normally Scottish Credit and Qualification Framework