PhD Studentship - Data-driven Catalyst Design: Integrating Quantum Chemistry and Machine Learning

How to apply: uom.link/pgr-apply-2425

No of positions: 1

This 3.5 year PhD project is fully funded and open to home students and overseas applicants. The successful candidate will received an annual tax free stipend set at the UKRI rate (£19,237 for 2024/25) and tuition fees will be paid. We expect the stipend to increase each year.

This PhD project aims to transform catalyst design by integrating quantum chemistry (QM), machine learning (ML), and high-throughput experimentation (HTE). The objective is to develop a data-driven framework that enhances the efficiency and effectiveness of catalyst development processes. By leveraging advanced computational methods alongside experimental data, this approach seeks to streamline the identification and optimisation of catalysts, ultimately benefiting various applications within the chemical industry.

Candidates should possess a BSc (at least a 2.1 honours degree) or an MSc in Chemistry. A strong competence in computational chemistry is essential, along with a genuine enthusiasm for research and creativity. Applicants should demonstrate the ability to work independently while also being effective team players. Proficiency in English is required, with a minimum IELTS score of 6. Additionally, a commitment to working within highly diverse and multicultural research groups is crucial. Knowledge of machine learning and quantum mechanics will be advantageous for this role.

To apply, please contact the supervisor, Dr Cristina Trujillo  - cristina.trujillodelvalle@manchester.ac.uk. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.

Advert information