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Exploring chemical space for computational materials discovery


   Chemistry

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  Prof Graeme Day  No more applications being accepted  Competition Funded PhD Project (UK Students Only)

About the Project

Supervisory Team:    Prof. Graeme Day

Project description

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. One of the great challenges for these methods is to decide which molecules to assess. The space of all possible molecules is huge, making exhaustive assessment of all possible molecules in this chemical space impossible. This project will develop

methods for efficiently navigating within chemical space to identify new molecules whose crystal packing will lead to promising properties. We have recently shown that it is possible to use crystal structure prediction for high throughput assessment of molecules (see Chemistry of Materials 2018, 30, 13, 4361–4371), and we have coupled this with evolutionary methods to find the best candidate molecules (see Chemical Science 2020,11, 4922-4933). You will continue the development of these methods, applying them to a range of materials discovery projects in the areas such as photocatalysis (see Journal of Materials Chemistry A, 2020,8, 7158-7170) and porous materials for gas storage or separations (see Nature 2017, 543, 657–664).

The project is based in the computational materials discovery research group led by Prof. Graeme Day http://www.crystalstructureprediction.net in the School of Chemistry at the University of Southampton, who have pioneered the use of CSP

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.

If you wish to discuss any details of the project informally, please contact Graeme Day, Email: [Email Address Removed].

Entry Requirements

Applicants should hold, or expect to obtain, a good degree (equivalent to a UK first or upper second class) in chemistry, materials science or a related discipline

Closing date: applications should be received no later than 31 August 2021 for standard admissions, but later applications may be considered

depending on the funds remaining in place.

Funding: full tuition fees for UK students plus for UK students, an enhanced stipend of £15,285 tax-free per annum for up to 3.5 years.

How To Apply

Applications should be made online, please select the academic session 2021/22 “PhD Chemistry (Full time)” as the programme. Please enter Graeme Day under the proposed supervisor.

Applications should include:

Curriculum Vitae

Two reference letters

Degree Transcripts to date

Apply online: https://www.southampton.ac.uk/courses/how-to-apply/postgraduate-applications.page

For further information please contact: [Email Address Removed]

 


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