Strategic Optimization of Machine Learning-based Metocean Forecasts, NERC GW4+ DTP PhD studentship for September 2025 Entry Ref: 5420

Supervisors

Lead Supervisor Ajit Pillai, University of Exeter, Engineering

Additional Supervisors

Ian Ashton, University of Exeter, Engineering

Location: Penryn Campus, University of Exeter

About the Partnership

This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP).  The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five Research Organisation partners:  British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology,  the Natural History Museum and Plymouth Marine Laboratory.  The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/

For eligible successful applicants, the studentships comprises:

• An stipend for 3.5 years (currently £19,237 p.a. for 2024/25) in line with UK Research and Innovation rates
• Payment of university tuition fees;
• A research budget of £11,000 for an international conference, lab, field and research expenses;
• A training budget of £1,000 for specialist training courses and expenses.

Project details

For information relating to the research project please contact the lead Supervisor via A.Pillai@exeter.ac.uk

Project Aims and Methods

This project partners a pioneering academic research team with the UK’s National Weather Service, to develop innovative methods for training machine learning (ML) weather prediction frameworks to improve meteorological and oceanographic (“metocean”) forecasts for marine and maritime applications. Traditional ML approaches learn from extensive datasets, which can be computationally demanding to use. This PhD research will therefore develop new strategies to optimize training, reducing data requirements while maintaining accuracy, enabling new approaches for regional metocean prediction. 
As data-driven weather prediction evolves, ML models trained on historical data could surpass traditional numerical weather prediction (NWP) methods in accuracy and efficiency. However, the assumption that longer training datasets improve model performance faces challenges, particularly in extreme conditions. The project will investigate optimizing training data quality over quantity, potentially reducing the computational cost and improving the pace of model development/deployment in application. 
The student will review existing ML practices in meteorological and oceanographic forecasting, benchmarking current methods, and proposing new training techniques. These may include varying the length of training data, using smaller models for specific seasons or regimes, and generating synthetic datasets. This research aims to disrupt current ML training practices by creating more efficient and accurate schemes for metocean forecasting. 

Project partners

The Met Office are meeting the extra expenses (such as travel and subsistence) incurred by the student visiting and working at the Met Office. They are also contributing to cash or in kind towards necessary materials whilst the student is based at the Met Office.

Training

The DTP offers funding to undertake specialist training relating to the student’s specialist area of research. 

Eligibility

NERC GW4+ DTP studentships are open to UK and Irish nationals who, if successful in their applications, will receive a full studentship including payment of university tuition fees at the home fees rate.

A limited number of full studentships are also available to international students which are defined as EU (excluding Irish nationals), EEA, Swiss and all other non-UK nationals.  For further details please see the NERC GW4+ website.

Those not meeting the nationality and residency requirements to be treated as a ‘home’ student may apply for a limited number of full studentships for international students. Although international students are usually charged a higher tuition fee rate than ‘home’ students, those international students offered a NERC GW4+ Doctoral Training Partnership full studentship starting in 2025 will only be charged the ‘home’ tuition fee rate (which will be covered by the studentship). 

International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. More information on this is available from the universities you are applying to (contact details are provided in the project description that you are interested in.

The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.
 

Equality, Diversity and Inclusion

The University of Exeter is committed to promoting and supporting equality, diversity, and inclusion within our working environments and is at the heart of all our activities.  With over 27,000 students and 6,400 staff from 180 different countries we offer a diverse and engaging environment where our diversity is celebrated and valued as a major strength. 
We actively encourage applicants with varied experiences and backgrounds and from all sections of the community regardless of age, race, ethnicity, sexual orientation, gender, religion, or disability status.  We are committed to creating an inclusive culture where all members of our community are supported to thrive.
Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented within our postgraduate research student community.  Reasonable adjustments are available for interviews and workspaces.
 

Entry requirements

Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK.   Applicants with a Lower Second Class degree will be considered if they also have Master’s degree.  Applicants with a minimum of Upper Second Class degree and significant relevant non-academic experience are encouraged to apply.

All applicants would need to meet our English language requirements by the start of the  project http://www.exeter.ac.uk/postgraduate/apply/english/.

How to apply

Apply now

In the application process you will be asked to upload several documents.  Please note our preferred format is PDF, each file named with your surname and the name of the document, eg. “Smith – CV.pdf”, “Smith – Cover Letter.pdf”, “Smith – Transcript.pdf”.

• CV
• Personal Statement (Please use the template in the link provided)
• Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim transcript if you are still studying.
• If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English, please see the entry requirements for details.
• Two references

Reference information
You will be asked to submit two references as part of the application process.  If you are not able to upload  your reference documents with your application please ensure you provide details of your referees.  If you provide contact details of referees only, we will not expect receipt of references until after the shortlisting stage. Your referees should not be from the prospective supervisory team.

If you are shortlisted for interview, please ensure that your two academic referees email their references to the pgradmissions@ex.ac.uk, 7 days prior to the interview dates. Please note that we will not be contacting referees to request references, you must arrange for them to be submitted to us by the deadline.

References should be submitted by your referees to us directly in the form of a letter. Referees must email their references to us from their institutional email accounts. We cannot accept references from personal/private email accounts, unless it is a scanned document on institutional headed paper and signed by the referee.

All application documents must be submitted in English. Certified translated copies of academic qualifications must also be provided.

The closing date for applications is Midnight 13th January 2025. Interviews will be held between 24 February and 7 March 2025.  

For more information about the NERC GW4+ DPT please visit https://nercgw4plus.ac.uk

If you have any general enquiries about the application process please email pgrapplicants@exeter.ac.uk.  Project-specific queries should be directed to the lead supervisor.

Data Sharing
During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

• the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;
• administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.

Summary