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of TB this country. This project is part of an exciting new Doctoral Training Programme in Microbial Genomics for Health Protection in collaboration with the UK Health Security Agency (UKHSA). This is
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School/Faculty: Computer Science Eligibility: UK/International Funding: School of Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780
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for distribution electric propulsion. Who we are looking for We are looking for enthusiastic, self-motivated applicants with first-class degree in Electrical Engineering, Aerospace Engineering or Computer
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Training Programme in Microbial Genomics for Health Protection in collaboration with the UK Health Security Agency (UKHSA). This is funded by NIHR as part of a Health Protection Unit in Public Health
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bioinformatic tools and focused on clear interpretation and communication of this data. This project is part of an exciting new Doctoral Training Programme in Microbial Genomics for Health Protection in
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Physics, Theoretical physics, Maths or other closely related subject (e.g. Materials Science with evidence of strong computational background and skills). To apply, please contact the supervisors; Dr Thomas
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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programme. Details of how to apply for the PhD programme are available at this page: https://www.sheffield.ac.uk/postgraduate/phd . When you apply, you should include the supporting documents relevant
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? Mechanical seals are critical components in high-pressure storage solutions for hydrogen and carbon capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational
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Programme Overview This PhD is part of the Engineering Hydrogen NetZero (EnerHy) Centre for Doctoral Training (CDT), a newly established EPSRC-funded initiative focused on advancing research and