University of Nottingham 
Nottingham, United Kingdom Angebotszusammenfassung
The University of Nottingham invites applications for two fully funded PhD studentships in Machine Learning for Sustainable Chemistry, commencing October 2027. These positions focus on developing interpretable machine learning models and data-driven strategies to predict green chemistry metrics, supporting AI-augmented assessments of synthetic routes. Supervised primarily by Professor Jonathan Hirst, the projects are supported by a Royal Academy of Engineering award and involve collaboration with synthetic chemists. One studentship includes a business development component, co-supervised by the Business School, focusing on AI technology business models and market routes. The role offers experience in programming and algorithm application within chemistry. Funding covers stipends at the RCUK rate of £21,805 per annum plus tuition fees for UK rates; international students must cover fee differences. Applications should initially contact Professor Hirst before formal submission.
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Projektbeschreibung
PhD Studentships: Machine learning for sustainable chemistry
Area
Chemistry
Location
UK Other
Closing Date
Monday 28 December 2026
Reference
SCI3073
Applications are invited for two PhD Studentships, starting October 2027, in the School of Chemistry at the University of Nottingham. The projects will focus on the development of new interpretable and interactive machine learning models and data-driven strategies for predicting consensus green chemistry metrics, enabling researchers to make AI-augmented rational assessments of different chemical synthetic routes.
The research will be supervised primarily by Jonathan Hirst and is part of a major award from the Royal Academy of Engineering Chairs in Emerging Technologies scheme, in which we have developed an open-source electronic lab notebook, deployed on the cloud at ai4green.app ai4green.app. The projects will involve close collaboration with synthetic chemists with a specific focus on green and sustainable chemistry. The studentships will provide a range of experience in computer programming and the development and application of machine learning algorithms to chemistry.
One of the studentships will have a significant business development component in the vein of an ‘evangelist developer’, i.e., someone who is technically skilled but also interested in promoting uptake of the software. This project is planned to be run in collaboration with and co-supervision from the Nottingham University Business School, with one of the strands of research focusing on understanding emerging AI-based technology business models, knowledge exchange processes and routes to market.
Funding notes: The studentships are fully funded for 42 months. Stipend at the RCUK rate (currently £21,805 per annum) and tuition fees will be paid at the UK rate. International students will have to pay the difference between UK and international fees.
Deadline: review of applications will start on Monday 7th December, 2026, and the positions will be filled as soon as suitable persons have been found; hence you are encouraged to apply as soon as possible.
To apply, students should initially contact Professor Hirst, Email: jonathan.hirst@nottingham.ac.uk, after which a formal application can be made via the University web site at:
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