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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
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dynamic soil moisture map that reflects weather changes. By developing digital dynamic soil moisture maps, decision support systems for route planning can be used to optimize the balance between forest
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for real-time decision-making and optimization under uncertainty. Develop techniques for computationally efficient mixed-integer stochastic optimization. Investigate the interplay between energy consumption
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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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to develop your scientific skills and concepts and effectively communicate the results of your research both verbally and in writing. This position also involves teaching at Chalmers’ undergraduate level
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. The project revolves around developing Traident – a new method to resolve the species origins and compositions of complex RNA sequence data. This will extend Kraken2 with analyses of ribosomal RNA and microRNA
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computational tools developed by our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel the anthropogenic and natural processes, and their relative
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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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values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your
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diverse community of individuals from a wide range of nationalities. As a PhD student with us, you benefit from comprehensive career development support, opportunities for networking, and access to robust