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, monitoring and inspections open up new possibilities, but also new challenges. In this context, the project will address challenges in linking collected data to current status, future deterioration and
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of Electrical Engineering, Division of Electric Power Engineering. The position will include characterising commercial cells and the production maturity through performance testing, teardown analysis and material
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candidate will join the Scientific Machine Learning group at TDB and SciLifeLab. The group develops theory, methods and software for data-driven science, with a current focus on uncertainty quantification
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Engineering, Computer Engineering, Mechatronics Engineering, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering or other related subjects. Experience working on experimental
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Do you want to contribute to the future of AI-driven electric transport systems? Join our research group to develop advanced machine learning methods for electromobility, focusing on energy-aware
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engineering Engineering » Electrical engineering Engineering » Materials engineering Engineering » Other Technology » Energy technology Researcher Profile Recognised Researcher (R2) Application Deadline 16 Aug
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refinement (TOPAS, GSAS-II, FullProf), ideally total scattering and pair distribution function analysis. Molecular conductors, radical and charge-transfer salts, or oxocarbon electrode chemistry. Synchrotron
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Engineering » Electrical engineering Technology » Telecommunications technology Researcher Profile Recognised Researcher (R2) Application Deadline 31 Aug 2026 - 21:59 (UTC) Country Sweden Type of Contract
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to develop resilient solutions for the future. About the research project The rapid growth of electric vehicles (EVs) is transforming road transport but also creates new challenges for both transport
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for your students, your research, and society at large. The Robotics and Artificial Intelligence subject (RAI) (www.ltu.se/robotics ) at the Department of Computer Science, Electrical and Space