21 parallel-and-distributed-computing "DIFFER" PhD positions at Chalmers University of Technology
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gradually become a cornerstone of modern life. Its success depends on immense computational effort and extended training times to produce sophisticated models. To handle the scale of these models, distributed
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Are you interested in developing computational tools to understand the detailed mechanical behaviour of multi-phase materials? Then this PhD position at Chalmers University of Technology might be
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We invite applications for several PhD positions in experimental quantum computing with superconducting circuits. You will work in the stimulating research environment of the Wallenberg Centre
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Advance Fall Risk Prediction and Rehabilitation with Cutting-Edge Sensing Technologies! Are you passionate about research that makes a real difference in people’s lives and society? Do you thrive
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state-of-the-art knowledge in the different disciplines taught by leading researchers in the field. Through an ambitious program with research visits, partner universities, and visiting lecturers
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degree is accepted. Excellent grades in computer networks, distributed systems, or cybersecurity courses Strong programming language skills Strong written and verbal communication skills in English The
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a complementary team that will work together to investigate different aspects of transceivers. Your responsibility will be to investigate multibranch receiver concepts that break the limitations
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to: design and perform experiment in different labs develop hand-on skills to fabricate high-performance battery You are expected to develop your own scientific concepts and communicate the results of your
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cells. Reference number: 20250273 Application deadline: August 10, 2025 Project overview This 5-year PhD project aims to develop a flexible and general model that enables comparison between different
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive