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University of Leeds Materials Science PhD Projects, Programs & Scholarships

We have 13 University of Leeds Materials Science PhD Projects, Programs & Scholarships

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  EPSRC CDT in Nuclear Energy - GREEN (Growing skills for Reliable Economic Energy from Nuclear)

Funding Type

PhD Type

The GREEN CDT is a consortium of the five universities of Lancaster, Leeds, Liverpool, Manchester and Sheffield, which aims to train the next generation of expert nuclear scientists and engineers.
  EPSRC Centre for Doctoral Training in Soft Matter for Formulation and Industrial Innovation (SOFI2 CDT)

Funding Type

PhD Type

16 fully funded, four-year PhD studentships are available in the EPSRC Centre for Doctoral Training in Soft Matter for Formulation and Industrial Innovation (SOFI2 CDT) commencing in September 2019, for graduates in the physical and biological sciences, mathematics and engineering.
  Synthetic Virology: Development of gene delivery vectors/synthetic vaccines
  Research Group: Astbury Centre for Structural Molecular Biology
  Prof P G Stockley
Applications accepted all year round

Funding Type

PhD Type

There is worldwide interest in exploiting our modern understanding of genomics to target gene expression therapeutically via a variety of mechanisms, such as transgene insertion and CRISPR-Cas gene editing.
  EPSRC Centre for Doctoral Training in Molecules to Product

Funding Type

PhD Type

50 funded PhD studentships will be available over the next 5 years for UK and EU students. The Centre for Doctoral Training in Molecules to Product will train tomorrow's research leaders with the skills and know-how in designing, characterising and developing the next generation of chemical and material based products.
  Developing AI approach to autonomous dismantling/packaging of nuclear installations
  Dr X Jia, Prof Shane Xie
Applications accepted all year round

Funding Type

PhD Type

At some stage in the decommissioning of nuclear installations (e.g., reactors and gloveboxes), it is inevitable that large metal structures (e.g., reactor vessels, gloveboxes, structural components) need to be cut into smaller pieces to be packed in containers, for temporary storage or permanent disposal or simply for transportation.
  Feedback-responsive protocells
  Dr P Beales
Applications accepted all year round

Funding Type

PhD Type

Feedback in chemical systems can give rise to clocks, bistable switches or oscillations; all of these features are employed by living cells in order to generate robust decisions and outputs while existing in a deafening background of thermodynamic noise.
  Metallosupramolecular assemblies and metal-organic frameworks
  Dr M Hardie
Applications accepted all year round

Funding Type

PhD Type

Nanometre-sized polyhedral or prismatic chemical architectures can self-assemble from combinations of transition metal cations and multifunctional ligands.
  Magnox sludge immobilisation in bespoke acid-based geopolymers
  Dr S Bernal, Dr S Adu-Amankwah, Dr L Black
Applications accepted all year round

Funding Type

PhD Type

Disposal of magnesium-bearing intermediate level waste sludge arising from reprocessed spent fuel from Magnox reactors in the UK presents significant decommissioning challenges.
  Multi-Objective Optimisation for Sustainable Steel Structures Employing Artificial Intelligence
  Dr KD Tsavdaridis
Application Deadline: 1 October 2019

Funding Type

PhD Type

This project will engage with Artificial Intelligence (AI) methods recently developed for structural engineering applications, as is proving to be an efficient alternative approach to classic modelling techniques, and attempt to reduce the percentage of uncertainty of the results as well as saving significant human time and effort spent in experiments.
  Computer Simulations of Biological Macromolecules
  Dr SA Harris, Dr D Read
Applications accepted all year round

Funding Type

PhD Type

Computational models are invaluable for visualisation in molecular biology, as they employ our best quantitative physical understanding of biomolecules and their interactions to predict their dynamics, which is often missing from biophysical experiments.
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