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NERC GW4+ DTP PhD Studentship - Machine Learning, Synthesis and Transport Mechanisms: A Holistic Approach to Aquatic Toxicity Prediction


Department of Chemistry

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Dr Matthew Grayson No more applications being accepted Competition Funded PhD Project (Students Worldwide)

About the Project

This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP) for entry in October 2021.

The GW4+ DTP consists of the Great Western Four alliance of the Universities of Bath, Bristol and Exeter and Cardiff University plus five prestigious Research Organisation partners: British Antarctic Survey, British Geological Survey, Centre for Ecology & Hydrology, the Natural History Museum and Plymouth Marine Laboratory. The partnership aims to provide a broad multi-disciplinary training, designed to produce tomorrow’s leaders in earth and environmental science.

SUPERVISORY TEAM:

Lead supervisor: Dr Matthew Grayson, University of Bath, Department of Chemistry https://researchportal.bath.ac.uk/en/persons/matthew-grayson
Co-supervisors: Prof Varinder Aggarwal (Bristol) and Dr Lee Bryant (Bath)

OVERVIEW OF THE RESEARCH:

Project Background

Animal testing has traditionally been used to assess the safety of chemicals. However, more sustainable approaches to safety testing are required due to the ethical concerns, costs and time scales associated with in vivo methods. Global industrialization has resulted in organic pollutants entering aquatic environments. To reduce the number of animals used in toxicity testing, new approaches are required that can assess the potential of organic compounds to cause harm to aquatic life. For such compounds, chemical reactivity contributes significantly towards their toxicological profile through covalent modification of biological nucleophiles. Our previous work led to the development of a fast, computational method for assessing the mutagenic risk of pharmaceutically important organic electrophiles (J. Chem. Inf. Model. 2019, 59, 5099). DFT-derived LUMO energies and activation barriers for reaction between a model nucleobase and electrophiles showed significant predictivity for the assessment of mutagenic potential. However, DFT calculations are time-consuming and expert-technical knowledge is required to perform them.

Project Aims and Methods

In this project, machine learning (ML) models will be developed that can, once trained, rapidly and easily predict reactivity descriptors for use in the prediction of aquatic toxicity. This work will lead to a new ML protocol for computationally assessing the toxicity of pollutants. Collaboration with Prof. Aggarwal, as a co-supervisor for the project, will focus on validating the new in silico prediction models. Predictions about the reactivity of novel electrophiles will be made using these models which will then be tested in the Aggarwal lab at Bristol. Close agreement between the computationally predicted and experimentally determined reactivity for this external test set will provide confidence in using these predictive models in chemical risk assessment. Collaboration with Dr Bryant, as a co-supervisor for the project, will focus on the mass-transport mechanisms by which organic compounds enter aquatic environments on catchment and system scales, using a local drinking-water-supply reservoir as a project study site. Dr Bryant will also support the investigation of the transport and distribution of organic compounds within the water and sediment components of an aquatic system.

CANDIDATE REQUIREMENTS:

Applicants for a studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an area appropriate to the skills requirements of the project. Experience of coding (any language) is desirable but not essential.

APPLICATIONS:

Enquiries relating to the project should be directed to Dr Matthew Grayson, [Email Address Removed].

Enquiries relating to the application process should be directed to [Email Address Removed].

Candidates should apply formally using the University of Bath 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=0015

When completing the form, please state in the ‘Finance’ section that you wish to be considered for NERC GW4+ DTP funding and quote the project title and lead supervisor’s name in the ‘Your research interests’ section. If you wish, you may apply for more than one project within the same application but you should submit a separate personal statement for each one.

If you have settled or pre-settled status under the EU Settlement Scheme, please upload documentary evidence with your application.

More information on how to apply may be found here:
https://www.bath.ac.uk/guides/how-to-apply-for-doctoral-study/

Funding Notes

Studentships cover tuition fees at the ‘Home’ level, research/training costs and a stipend (£15,285 p.a., 2020/21 rate) for 3.5 years.

Candidates normally eligible for 'Home' fees are:
UK nationals*
Irish nationals living in the UK/Ireland
Applicants with settled or pre-settled* status in the UK under the EU Settlement Scheme
Applicants with indefinite leave to enter/remain in the UK

* must have lived in the UK/EEA/Switzerland continuously since September 2018.

International applicants, not eligible for ‘Home’ fees, may apply and will be considered for a limited number of fee discounts equivalent to the difference between the ‘Home' and ‘Overseas’ tuition fees.


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