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Postgraduate research project

Crystal structure prediction of imperfectly ordered materials

Funding
Fully funded (UK only)
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date

About the project

A fully funded PhD studentship is available in the area of computational materials discovery, as part of a prestigious international Synergy grant funded by the European Research Council. The project, ‘Autonomous Discovery of Advanced Materials’, aims to revolutionise the way that new materials are discovered by combining computational simulations, robotics and materials synthesis.

Within this studentship, you will develop computational methods that can guide the discovery of new materials. Computational methods are developing rapidly in this area, with the use of crystal structure prediction to assess molecules for their likely crystal packing and resulting materials properties. Current methods that are used to predict the structures of molecular crystals almost exclusively model perfect crystals, while real materials contain defects, impurities and disorder.

This project will develop methods for predicting imperfections, as well as amorphous structures and mixed crystals (where two molecules make up a crystal structure with sites within the structure randomly occupied by either molecule). Results of the calculations will be used to inform experiments and help understand the role of imperfections on relevant materials properties.

The project is based in the computational materials discovery research group led by Professor Graeme Day in the School of Chemistry at the University of Southampton, who have pioneered the use of crystal structure prediction for the discovery of functional molecular materials. You will be part of a multi-disciplinary team which includes collaborators at the University of Liverpool and Rostock University. Through these collaborations, you will interact with other computational chemists, synthetic chemists and engineers developing the use of robots in the materials chemistry laboratory.

We are looking for candidates with an enthusiasm for research, multidisciplinary collaboration and tackling challenging problems through teamwork. You do not need to have experience with crystal structure prediction methods. Experience with computational chemistry and programming would be an advantage, as well as excellent presentation skills.

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