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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 3 months ago
and £21.7 billion committed by the UK government over 25 years, the UK is positioned to lead in CCUS. However, the success of these clusters depends on the adoption of safe and cost-effective
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per year for 3.5 years. Lead Supervisor’s full name & email address Dr Massimiliano Fasi: m.fasi@leeds.ac.uk Project summary The growing importance of artificial intelligence is fostering a paradigm
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of the alternative material supplier base to meet market demand, and will lead the creation of a preliminary guidance document for the use of recycled plastics and alternative materials in lateral flow cassettes
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, management, quantitative analysis Lead in publication outputs in appropriate academic and industry fora The role-holder will also have management, liaison and networking responsibilities. The skills
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lead to transformational developments for the chemical industry and associated energy technologies. This project, which is funded by the Royal Academy of Engineering, will involve the selection
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, management, quantitative analysis Lead in publication outputs in appropriate academic and industry fora. The role-holder will also have management, liaison and networking responsibilities. The skills
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aims and objectives are met. Working closely with the supervisory team, develop and plan research objectives. Present information on research progress and outcomes to, for example, project lead, funding
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: An intelligent ATM is an ideal solution to analyse and monitor the local device for possible physical or cyber threats. A typical ATM system is suitable to host such environments. A typical system, consisting of
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explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers the opportunity for the PhD student to lead the development of innovative simulation tools
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands