450 developer-"https:"-"https:"-"https:"-"Institut-Agro-Rennes-Angers" PhD positions in United Kingdom
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supply chain resilience. Following a PhD‑by‑papers route, the research aims to deliver three high‑quality scholarly outputs and develop insights to enhance supply chain management practise. This project
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systems, and digital twin technologies. The project will contribute to the development of intelligent collaborative machines for next-generation manufacturing systems. What will you be doing? Investigating
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gammopathy of undetermined significance (MGUS). However, only 1% of patients with MGUS will develop myeloma every year. Despite advances in treatments, myeloma continues to be associated with significant
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performance. This PhD project aims to develop a data-driven framework for graphene aerogel design by integrating structured experimental Design of Experiments (DoE) with machine learning (ML). The student will
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. Specifically, we develop small molecule photo(cyclo)addition reactions that allow for the efficient formation of covalently bound reaction products under (visible) light irradiation. Importantly, the thus formed
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early detection and predict adverse pregnancy outcomes. You will develop and validate a data-driven clinical decision support tool in collaboration with clinicians and industry partners. Pre-eclampsia is
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this, empirical rules have been developed. However, a fundamental understanding of the process is still lacking. Furthermore, current standard tests do not adequately capture the phenomena, and thus industry is
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such as virtual reality are being used to increase motivation and adherence to exercise programmes without the need for in person contact. This work builds on our existing co-development and implementation
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develop advanced skills in qualitative research, stakeholder engagement, and knowledge exchange, alongside being supported to publish in leading journals and present at conferences. You will also benefit
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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density