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work in a strong theory–experiment environment, enabled by our close collaboration with the Wallenberg Centre for Quantum Technology (WACQT) and its experimental teams developing superconducting
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computer science, mathematics, electrical engineering, or a relevant area research experience, preferably in programming languages, compilers, applied mathematics, and optimization techniques a strong background in
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generalist engineering school within the IMT (Institut Mines-Télécom)—France's primary group of engineering schools aims to support major transitions, train responsible engineers, and place scientific and
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integration, and system integration for next-generation wireless systems. We envision programmable and intelligent cellular networks that can be dynamically and algorithmically instrumented and optimized
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of the corresponding manufacturing processes. The selected candidate will be responsible for: Leading the formulation development of the solid diagnostic product. Designing and optimizing the manufacturing process
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relations and recruiting operations for the College of Engineering, developing strategic initiatives and managing year-round employer services and systems. Serve as the primary liaison with employers, create
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Electrical Engineering or Physics or Materials Science. Experience on numerically modeling light-matter interactions, designing photonic devices, and employing optimization approaches. Experience in project
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will define the optimal values for a range of key parameters and explore how these differ for various turndown ratios and fuel blends. This will be applicable to gas turbine power stations, enabling them
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capabilities, existing technology can only handle relatively small-scale problems. Information In the SymBi project (Exploiting Symmetries for Faster Bilevel Optimization Algorithms), we address this limitation
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advancing the technology to a higher TRL level (from 2 to 5). The activities to be carried out under this scholarship correspond to WP2, Task 2.5, which involves experimental testing aimed at optimizing