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methods/simulations, state-of-the-art computational techniques (e.g. data-driven methods and/or FEM) and/or theoretical material modeling will be given preference We offer: chance to collaborate with
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limiting their ability to perform essential daily tasks. This interdisciplinary PhD project aims to design a new generation of soft exoskeletons using smart textiles, driven by artificial intelligence (AI
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materials that can host an innovative form of AI which operates in hardware. This technology, called neuromorphic computing, aims to surpass the limitations of current software-based AI models, especially in
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, preferably experience with genetic engineering of model bacteria, like Bacillus subtilis fluorescence microscopy interest in chronobiology (circadian biology) ability to work in a highly collaborative
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consisting of PAT and mechanistic / data driven modelling allowing process control. Steps to be taken will be: Developing a process applicable PAT method (single / multisensoric) for AAV / LNP / VLP detection
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chemistry and food technology to molecular and data- driven nutrition (Precision Nutrition). In Food Science, we focus primarily on marine and plant-based food systems for which we develop tools and processes
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chemistry and life cycle thinking in early decision-making. AI-based methods and hybrid models, which integrate data-driven and mechanistic modelling, hold significant potential to enhance prospective
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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PhD Studentship: Optimisation of Liquid Metal Filtration and Cleanliness in Nickel Based Superalloys
-supervision by Dr Mark Hardy. The industry aligned EPSRC DigitalMetal CDT offers a four year training programme on integrating data driven with physics-based models of products equipping students with
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which