PhD Studentship: Machine learning for sustainable chemistry

 PhD Studentship: University of Nottingham, UK

Applications are invited for a PhD Studentship, starting December 2020 or soon thereafter, in the School of Chemistry at the University of Nottingham. This project 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. 

Supervisor: Jonathan Hirst

Funding notes: The studentship is fully-funded for 48 months. Stipend at the RCUK rate (currently £15,285 per annum) and tuition fees will be paid at the UK/EU rate. International students will have to pay the difference between UK/EU 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 16th November, 2020, and the position will be filled as soon as a suitable person has 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 ,

 


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