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Computational Studies of Novel Functional Materials

Department of Chemistry

Liverpool United Kingdom Computational Chemistry Data Analysis Inorganic Chemistry Computer Science Mathematics Physical Chemistry Synthetic Chemistry

About the Project

The PhD position is funded by the Leverhulme Centre for Functional Materials Design at the University of Liverpool via the Leverhulme Trust. The centre aims to bring together chemical knowledge with state-of-the-art computer science and automated technologies to develop a new approach to revolutionize the design of functional materials at the atomic scale.

The step-changing advances in technology that bring new electronics, faster computers, higher efficiency solar cells, higher performance catalysts and batteries that store more energy are possible thanks to the discovery of better functional materials. This discovery process is difficult because of the vast number of possible combinations of chemical elements in the periodic table and their ratios that can potentially form a material. Further, the underlying interactions are complex, and need to be accurately taken into account to computationally assess whether a certain arrangement of atoms is stable.

In our group we have developed highly novel Crystal Structure Prediction methods that use chemical knowledge and design principles to build novel crystal structures from untried combinations of elements. This approach gives an opportunity to access more complex and potentially more interesting materials with desirable electronic or thermal properties. Following the recent success of these knowledge-based methods in CSP [1-3] and the ongoing work in the group to implement advanced computer science techniques to accelerate them, we are looking for highly motivated researchers who wish to push the boundaries of CSP working on testing, development and application in a wide range of different chemistries.

The ideal candidate will have a strong materials background through a degree in physics, chemistry, materials science or engineering, as well as good programming skills. The successful applicant will work closely with our very strong teams of computational chemists, computer scientists, inorganic chemists, physicists and material scientists to develop ways of predicting and analysing new materials. Our success arises from a close working relationship between computational and experimental researchers within the group, which is part of the Leverhulme Centre for Functional Materials Design (, where researchers with physical science and computer science backgrounds collaborate closely. The successful candidate will work in this cross-disciplinary environment, using their computational skills in close collaboration with the experimental expertise within the research group, to accelerate the discovery of new functional materials.

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

Applications can be made at any time and will be considered when they are received. Informal enquiries should be made to Dr George Darling (). For more details regarding application, please see

To apply please visit: Please quote reference CCPR016 in the funding section of the online application form.

Funding Notes

The award is primarily available to UK students and will pay full tuition fees and a maintenance grant for 42 months (£15,609 for 2021/2022). EU and non-EU students are eligible to apply but would need to have their own funding to cover the difference between the UK and international tuition fees. Please refer to our Fees and Funding webpage View Website. EU students starting before 1st October 2021 may be eligible for the reduced UK fee rate.


[1] C. Collins, MS. Dyer, MJ. Pitcher, GFS. Whitehead, M. Zanella, P. Mandal, JB. Claridge, GR. Darling and MJ. Rosseinsky (2017) Accelerated discovery of two crystal structure types in a complex inorganic phase field. Nature, 546 (7657) 280 - 284.
[2] C. Collins, GR. Darling, and MJ. Rosseinsky (2018). The Flexible Unit Structure Engine (FUSE) for probe structure-based composition prediction. Faraday discussions. doi:10.1039/c8fd00045j
[3] PM. Sharp, MS. Dyer, GR. Darling, JB. Claridge, and MJ. Rosseinsky (2020). Chemically directed structure evolution for crystal structure prediction. Physical Chemistry Chemical Physics, 22 (32), 18205-18218.

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