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Using Machine Learning to Access Challenging Hydrogenations: A combined theoretical and experimental approach


   Department of Chemistry

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  Dr Ruth Webster, Dr Matthew Grayson  No more applications being accepted  Funded PhD Project (Students Worldwide)

Bath United Kingdom Artificial Intelligence Computational Chemistry Inorganic Chemistry Machine Learning Organic Chemistry Pharmaceutical Chemistry Synthetic Chemistry

About the Project

The University of Bath is inviting applications for the following funded PhD project supervised by Dr Ruth Webster and Dr Matthew Grayson in the Department of Chemistry.

This project will use state of the art machine learning (ML) methodologies, coupled with synthesis to probe the conditions necessary to undertake efficient asymmetric hydrogenations to form 1,2-contiguous stereocentres. These are valuable organic motifs unlikely to be accessible using a traditional screening approach. The easiest way to access 1,2-contiguous stereocentres is to undertake an asymmetric hydrogenation (AH) of tetra-substituted carbon-carbon double bonds (TSC=Cs) (the C=C itself is easy to prepare using catalytic metathesis or Wittig chemistry). The importance of AHs is demonstrated by the 2001 Nobel Prize in Chemistry being awarded to Noyori and Knowles for their pioneering work in this area. However, although AHs of di/tri-substituted C=Cs have been extensively explored and are deemed facile transformations, the AH of TSC=Cs remains a formidable challenge.

This project involves a diverse mix of synthetic organic chemistry, catalysis, scale-up synthesis and state of the art ML techniques. During student placements at GSK, the student will have access to modern high throughput reaction screening and optimisation platform to rapidly generate results and test the models. This will leave the student well-rounded in synthesis and theory and with a diverse and highly desirable skillset.

Candidate requirements:

Applicants should hold, or expect to receive, an MChem/MSci/MRes degree in Chemistry (2.1 or higher), or the equivalent, and a desire to undertake both computational and lab-based synthetic studies is essential.

Non-UK applicants will also be required to have met the English language entry requirements of the University of Bath.

Enquiries and applications:

Informal enquiries are welcomed and should be directed to Dr Ruth Webster and/or Dr Matthew Grayson.

Formal applications should be made via the University of Bath’s online application form for a PhD in Chemistry.

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

Anticipated start date: 4 October 2021.


Funding Notes

Candidates applying for this project may be considered for a 4-year EPSRC Industrial CASE studentship with Glaxo SmithKline (GSK). Funding covers tuition fees, an enhanced stipend (2021/22 UKRI rate £15,609 per annum + £2,000 per annum top-up from the industrial partner) and a generous budget for research expenses, training and conference attendance. EPSRC iCASE studentships are open to both Home and International students; however, in line with guidance from UK Research and Innovation (UKRI), the number of awards available to International candidates will be limited to 30% of the total iCASE awards available to the university in 2021/22.
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