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their performance and support sustainable electrode processing. As part of this collaborative project, you will work in a multidisciplinary setting and engage with international researchers. Who we are looking
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introduces new and underexplored vulnerabilities to network-based threats. The goal of this research is to uncover such threats, evaluate their impact on training performance and model integrity, and develop
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universities. About the research project This PhD project is part of the interdisciplinary WASP-WISE NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through
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Team up with up to 3 fellow Ph.D. students in the DSP-assisted Wideband & Efficient Transceivers (SWEET) project which is part of the WiTECH center to perform cutting-edge multi-disciplinary
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NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through machine learning, computer vision, and materials science. The focus of this position is on
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safety. You will work on developing control algorithms all the way to performance assessment in test vehicles. The project combines theoretical aspects of control algorithms, experimental design, and
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Implement advanced numerical concepts and material models to describe damage initiation and progression in a multi-phase microstructure Use the numerical framework to perform numerical studies generating new
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Join us for an exciting and excellent PhD journey! Everyday user behaviour may affect the environmental performance of household appliances, yet it is often overlooked in environmental assessments
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strategies. Explore the technical, on-site, and managerial innovations and tools needed for contextualizing this ontology in Sweden. Perform action research and case studies in construction sites
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high-quality research on interpretable and learning-based stochastic optimal control for over-actuated electric vehicles, with a focus on ensuring robustness and fail-safe operation. You will: - Develop