PhD Studentship: Machine learning for sustainable chemistry

Updated: 3 months ago
Location: Nottingham, SCOTLAND
Job Type: FullTime
Deadline: 07 Oct 2020

Reference SCI1958

Closing Date Wednesday, 7th October 2020

Department Chemistry

Applications are invited for a PhD Studentship, starting October 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. 

The project will be supervised by Jonathan Hirst. In addition, there will be close interactions with a large community of chemists via the EPSRC-funded Prosperity Partnership “Accelerated Discovery and Development of New Medicines: Prosperity Partnership for a Healthier Nation” and the Centre for Doctoral Training (CDT) in “Sustainable Chemistry: Atoms-2-Products an Integrated Approach to Sustainable Chemistry”. The project will provide a range of experience in computer programming and the development and application of machine learning algorithms to chemistry. 

Funding notes: The studentship is fully-funded for 48 months. Stipend at the RCUK rate (currently £15,009 per annum) and tuition fees will be paid at the UK/EU rate. International students must 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 7th  September, 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:  , after which a formal application can be made via the University web site at: .

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