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Field
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This is an exciting opportunity to explore the role of complex microbial communities in promoting resilience and maximising yields in large scale algal bioreactors exposed to different environmental
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machine-learning surrogate models capable of delivering near-DFT (density functional theory) accuracy in just a few CPU seconds per structure. This approach will enable the high-throughput screening of tens
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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sequencing technologies - including metagenomics and transcriptomics - to explore the dynamic interplay between human gene expression and microbial communities. The successful candidate will develop and apply
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into hydrogen and nitrogen under practical onboard conditions. Successful candidate will develop and apply computational methods, such as density functional theory based atomistic modelling and machine learning
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detected. As a result, UKHSA’s Real-time Syndromic Surveillance Team are working with N/LAB at the Nottingham University Business School to explore whether we can use anonymised sales of pharmacy over
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model predictive control (MPC) methods to enable large groups of buildings to dynamically form coalitions and provide flexible energy services. Your work will incorporate advanced robust MPC techniques
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Evaluating the use of longitudinal over-the-counter healthcare sales data as a source of syndromic surveillance for community-based infections UK Health Security Agency and Nottingham University
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new sustainable femtosecond laser nanomanufacturing process to overcome the challenges of atomic sale precision, feature size and defects rates for quantum dots. In this project, molecular dynamics
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We invite applications for a fully funded PhD studentship (3.5 years) hosted by the University of Birmingham and conducted in collaboration with Siemens and the UK Met Office. This project is ideal