PhD Studentship: Machine learning for chemistry

at University of Nottingham
Published May 14, 2023
Location Nottingham, United Kingdom
Category Machine Learning  
Job Type Scholarship  


PhD Studentship: Machine learning for chemistry

Applications are invited for PhD Studentships, starting October 2023, in the School of Chemistry at the University of Nottingham. The PhD projects will focus on the development of new interpretable and interactive machine learning models and data-driven strategies aimed at addressing the molecular design problem of polymers with tuneable biodegradability.

The projects will be supervised by Jonathan Hirst, who currently holds a Royal Academy of Engineering Chair in Emerging Technologies. The projects will involve close collaboration with academic and industrial synthetic chemists with a specific focus on green and sustainable chemistry. The projects will provide a range of experience in computer programming and the development and application of machine learning algorithms to chemistry.

Funding notes: The studentships are fully-funded for 42 months. Stipend at the RCUK rate (currently £17,668 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.

Entry requirements: Applicants should have, or expected to achieve, at least a 2:1 Honours degree (or equivalent if from other countries) in Chemistry or a related subject. A MChem/MSc-4-year integrated Masters, a BSc + MSc or a BSc with substantial research experience will be highly advantageous. Experience in computer programming will also be beneficial.

If English is not the candidate’s first language, they must provide evidence before the beginning of the studentship that they meet the University minimum English Language requirements (IELTS 6.0 with at least 5.5 in each element).

Deadline: review of applications will start on Monday 12th June, 2023, and the positions will be filled as soon as possible thereafter; hence you are encouraged to apply as soon as possible.

To apply, students should initially contact Professor Hirst, Email: , after which a formal application can be made via the University web site at: