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of the project is to 1) develop computational pipelines for image analysis and physical analysis of cell shape trajectories, and for combined morpho-molecular analysis of cell shape together with molecular markers
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PhD level in an appropriate discipline, and you will have sufficient breadth or depth of knowledge in physical acoustics and information theory. You will have knowledge of appropriate research methods
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interview process. RCUK eligibility: No Eligibility: Strathclyde Business School is committed to supporting a diverse and inclusive postgraduate research population. We make decisions on entry by assessing
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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 3 months ago
. The research will be computational based, and at this stage is still broad, so we can formulate the optimal plan for the right candidate. We will take an interdisciplinary approach, and you will be able
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 3 months ago
, preparing them for a successful career in academia, industry, or entrepreneurship. Click Apply for more information on our application process. Deadline: 30th June.
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of 92.5% lithium-7 and only 7.5% lithium-6. As the tritium breeder blanket requires 30 to 90% lithium-6 enrichment, an isotope enrichment process is required. More than 100 tonnes of isotopically pure
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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
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elements like Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) to secure hardware components. Embedded Trust Protocols: Design protocols that establish and maintain trust within
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information from high-quality videos that share content with distorted footage as constraints in the learning process of modelling algorithms. This method uses the characteristics and knowledge embedded in high