Machine learning approaches to reaction design and optimisation

The University of Bath is inviting applications for a fully-funded PhD studentship in the Department of Chemistry under the supervision of Dr Matthew Grayson.

The synthesis of bespoke molecules is essential in meeting the global demand for new agrochemicals, consumer products, materials and pharmaceutical drugs. Trial-and-error has historically dominated reaction discovery but more cost effective, rapid and sustainable alternatives are becoming increasingly sought after.

The computational design of new reactions is regarded as one of the “Holy Grails” of computational chemistry. Although quantum mechanical (QM) calculations have been applied to reaction design, they are often much slower than traditional experimental screening methods which limits their use in reaction discovery. The need to exhaustively explore many different catalyst designs, substrate combinations and conformations using time-consuming QM calculations is the source of this poor efficiency.

This project, funded by AstraZeneca, will develop machine learning models that can rapidly predict the outcomes of catalytic reactions thus replacing the need to perform time-consuming QM calculations. The project will include a placement of at least 3 months at AstraZeneca in Macclesfield.

For information about the lead supervisor, see https://researchportal.bath.ac.uk/en/persons/matthew-grayson and https://thegraysongroup.co.uk/.

For information about research in the Department of Chemistry, see https://www.bath.ac.uk/topics/department-of-chemistry-research/

Candidate requirements:

Applicants should hold, or expect to receive, a First Class or good Upper Second Class Honours degree, or the equivalent from an overseas university. A master’s level qualification would also be advantageous. Experience with coding (any language) is desirable but not essential.

How to apply:

Informal enquiries are welcomed and should be directed to Dr Matthew Grayson ([Email Address Removed]).

Formal applications should be made via the University of Bath’s online application form for a PhD in Chemistry:
https://samis.bath.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RDUCH-FP01&code2=0014

More information about applying for a PhD at Bath may be found here:
http://www.bath.ac.uk/guides/how-to-apply-for-doctoral-study/

Anticipated start date: 28 September 2020.