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cavitation and the effects observed on biofilms and bacteria, and to understand these links, in order, in the long term, to optimize and control this type of therapy. The profile of the PhD student (M/F) must
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that can self-learn bulk visco-elastic properties? How to structure such materials to learn continually and counteract the aging of their own parts? Can we optimize self-learning materials to achieve
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through optimization of ion channels incorporation and activity in lipid bilayers. The project sits at the interface of biophysics, engineering and biochemistry. The PhD student will be part of
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for the green transition of the energy sector. Our research develops innovative digital tools and methods, combining cutting-edge AI, simulation, and optimization, to create smarter, more resilient, and
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replicate the sensory and functional qualities of natural seafood. This PhD project is expected to develop technology for cultivated seafood, by selecting the optimal cell source, developing a continuous cell
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organizational challenges of this twin transition. First, interoperability is key in the energy transition, requiring further integration of existing control and optimization systems. This transition makes energy
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, or conditional deletion of defined dendritic cell subsets, providing powerful genetic tools for dissecting cell-specific roles in vivo. Using and optimizing these tools to study Type 3 Dendritic cells in mouse
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first focus on hedging decisions with respect to the uncertainty on the battery model itself. To this end, you will explore concepts such as distributionally robust chance constrained optimization. Second
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level. Overseas students must be able to demonstrate they are able to pay the difference between UK and overseas fee. For 2025/26 entry this will be £22,714 per year of study. The project focuses
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sanitation industries. Working with our established industry partners, you'll implement your innovations in real operational environments, seeing your research make tangible difference while building