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properties of skeletal muscle during static and dynamic contractions. The student will also participate in early-stage algorithmic work to model muscle architecture and behavior across contraction types. In
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. The candidate will design algorithms that synchronize and fuse heterogeneous data sources to improve perception robustness under variable underwater conditions. Segmentation and classification: Training
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Localization and Mapping) algorithms to enable reliable navigation of the UUV relative to the USV and the environment. This includes handling the challenging conditions of subsea localization (limited GPS, murky
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for behavioural and security properties; efficient algorithms for model checking, learning and synthesis; improved explainability and safety of machine learning models, e.g. by integrating neural and symbolic
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of microalgal biomass. The PhD student will join the Life Cycle Sustainability (LCS) group and will collaborate with other international research partners. LCS brings together multiple competences within