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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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spectral inequalities and spectral optimization problems will also be explored. Job assignments You will conduct research in the group of Associate senior lecturer Simon Larson. You are expected
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before the application deadline* Demonstrate strong mathematical skills, particularly in optimization and algorithm development Have a publication record in peer-reviewed journals (e.g., IEEE Transactions
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learning, generative AI, and multi-objective optimization. Evaluate and select design options based on user-defined parameters such as environmental impact, aesthetic value, and cost. Additionally, you will
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that collaborate with humans for societal improvement. You will apply for funding and lead research initiatives in areas such as perception, planning, optimization, testing, and verification, producing high-impact
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will consist in the porting and optimization of parallel and heterogeneous programming models for the upcoming multiprocessor systems developed in the DARE project . The focus of DARE are long vector
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covers various solid dynamics topics, including vibrations, fatigue, wear, contact mechanics, wave propagation, optimization, and smart materials. We employ a mix of theoretical modeling, numerical methods
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artificial intelligence), exploring future skills, and optimizing equipment management. You will work in close collaboration with major industry partners to collect and analyze real-world empirical data using
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for describing and reasoning about algorithms for translating from quantum circuits to pulse schedules, and optimizations that can be performed on the pulse schedule level, while at the same time following known