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-terrestrial networks where communication signals will be linked via satellites. A portion of the communication signals will be reflected from the Earth's surface and can be received by satellites in the same
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fundamental problems related to the design and optimisation of next-generation network services, the candidate will formulate and demonstrate novel techniques for advanced and trustworthy communication networks
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
environment You will join the Communication Systems (CS) group within the Division of Communications, Antennas, and Optical Networks (CAOS) at the Department of Electrical Engineering . The group includes nine
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programming Excellent communication skills in English, both written and oral Ability to work independently, take initiative, and assume responsibility Strong collaborative skills, due to the interdisciplinary
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Join us for an exciting and excellent PhD journey to create the future of maintenance! Explore the fascinating future of Net Zero industries where complex and highly automated equipment need
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of Communication and Learning in Science, and join our graduate school Communication and Learning in STEM . At the division, we conduct research and education with a focus on teaching and learning, particularly in
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internationally recognised, and thus we are active members in the ALERT Geomaterials network and many international committees. Our international team with over 15 full-time researchers offers a great working
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networks, supply chain strategy, operations planning and control, material handling, and freight transport. Digitalisation, circularity, and resilience are key drivers and enablers of this research. Our goal
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Sustainability (WISE), Sweden's largest-ever materials science investment. Recruited researchers will join the WISE Research School, a national program offering seminars, courses, and international networking
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are unpredictable, e.g., unanticipated changes in the environment of the ACPS may cause a neural network to produce faulty outcomes that could endanger the safety of the system. To assure the safe and reliable