PhD Studentship : Machine learning of defect chemistry and dopability of mixed-anion semiconductors

This PhD project aims to reduce—by approximately an order of magnitude—the time and computational effort required to evaluate point-defect energetics in technologically important mixed-anion semiconductors (such as those used in thermoelectric devices and solar energy applications). Point defects play a critical role in determining electronic and ionic transport properties, stability, and device performance. However, calculating defect formation energies and migration barriers using first-principles methods remains a major bottleneck in the materials discovery process. To address this, we will develop machine-learning surrogate models capable of delivering near-DFT (density functional theory) accuracy in just a few CPU seconds per structure. This approach will enable the high-throughput screening of tens of thousands of potential materials. A key component of the project is the creation of a high-quality defect database for functional mixed-anion semiconductors, which will be used to train the machine learning models to predict defect behavior without the computational cost of DFT.

The successful applicant should have or expect to achieve at least a 2.1 honours or equivalent at Bachelors or Masters level in Chemistry, Physics, Materials Science, or a related discipline. The successful applicant will demonstrate strong interest and self-motivation in the subject and the ability to think analytically and creatively. Good computer skills, plus good presentation and writing skills in English, are required. Previous research experience in contributing to a collaborative interdisciplinary research environment is highly desirable but not necessary as training will be provided. Experience of computer modelling is desirable but not essential as full training will be provided in an active and well-resourced research group based in brand new state-of-the-art Chemistry laboratories at the rapidly growing University of Birmingham.

**NOTE** Applications must be made through the university’s on-line application system by clicking the 'Apply' button above. 

In addition, please provide: (1) a cover letter summarising your research interests and suitability for the position, and indicating with PhD project would be of interest; (2) the contact details of two people able to provide a letter of reference; and (3) a full curriculum vitae. Informal enquiries can be made to Professor Scanlon (d.o.scanlon@bham.ac.uk).

Funding notes:
This studentship is fully funded by UKRI for 3.5 years and includes a tax-free annual stipend (currently £20,780) and fees (currently £5,006) at the UK home rate. Due to funding restrictions, applicants not eligible for UK home fee status will only be considered in exceptional circumstances.

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