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Big data and machine learning for reaction design


   Department of Chemistry

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  Dr Matthew Grayson  No more applications being accepted  Competition Funded PhD Project (European/UK Students Only)

Bath United Kingdom Artificial Intelligence Computational Chemistry Data Analysis Machine Learning Organic Chemistry Computer Science Pharmaceutical Chemistry Synthetic Chemistry

About the Project

The University of Bath is inviting applications for the following PhD project commencing in October 2021.

Funding is available to candidates who qualify for ‘Home’ fee status. Following the UK’s departure from the European Union, the rules governing fee status have changed and, therefore, candidates from the EU/EEA are advised to check their eligibility before applying. Please see the Funding Eligibility section below for more information.

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.

Big data and machine learning offer new opportunities for the computational design of reactions. Machine learning models can, once trained, make predictions for previously unseen molecules in seconds. This project, in collaboration with AstraZeneca, will develop machine learning models that can rapidly predict chemical reactivity and selectivity thus replacing the need to perform time-consuming QM calculations. Our work will lead to a new high-throughput in silico approach to designing reactions.

The project will include a 3-month placement at AstraZeneca in Macclesfield.

Candidate Requirements:

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

Non-UK applicants must meet our English language entry requirement.

Enquiries and Applications:

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 (full-time).

More information about applying for a PhD at Bath may be found on our website.

Funding Eligibility:

In order to be considered for a studentship, you must qualify as a ‘Home’ student. In determining ‘Home’ student status, we follow the UK government’s fee regulations and guidance which, when available, will be set out by the UK Council for International Student Affairs (UKCISA) on their website. Although not yet confirmed, we expect that the main categories of students generally eligible for ‘Home’ fee status will be:

  • UK nationals (who have lived in the UK, EU, EEA or Switzerland continuously since September 2018)
  • Irish nationals (who have lived in the UK or Ireland continuously since September 2018)
  • EU/EEA applicants with settled status in the UK under the EU Settlement Scheme (who have lived in the UK continuously since September 2018)
  • EU/EEA applicants with pre-settled status in the UK under the EU Settlement Scheme (who have lived in the UK, EU, EEA, Switzerland or Gibraltar continuously since September 2018)
  • Applicants with indefinite leave to enter/remain in the UK (who have been resident in the UK continuously since September 2018)

EU/EEA citizens who live outside the UK are unlikely to be eligible for ‘Home’ fees and funding.

Additional information may be found on our fee status guidance webpage, on the GOV.UK website and on the UKCISA website


Funding Notes

A studentship includes ‘Home’ tuition fees, a stipend (£15,609 per annum, 2021/22 rate) and research/training expenses (£1,000 per annum) for up to 3.5 years. Eligibility criteria apply – see Funding Eligibility section above.
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