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University of Exeter

PhD Studentship: Hidden Aerosols of the Arctic – Uncovering Secondary Emissions from Blowing Snow (NERC GW4+ DTP, September 2026 Entry) University of Exeter in United Kingdom

Degree Level

PhD

Field of study

Machine Learning

Funding

Available

Deadline

Jan 8, 2027

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Country

United Kingdom

University

University of Exeter

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Keywords

Machine Learning
Chemistry
Environmental Science
Air Quality Management
Earth Science
Radiation Physics
Physics

About this position

[Home tuition fees covered plus annual tax-free stipend (£20,780 p.a. for 2026/27) for 3.5 years, £9,000 project costs budget, £2,000 conference budget, £1,000 individual training budget. CASE placement at the Met Office covers additional expenses.]

This PhD studentship, hosted by the University of Exeter and the British Antarctic Survey, offers an exciting opportunity to investigate the hidden aerosols of the Arctic and uncover secondary emissions from blowing snow. The project is part of the NERC GW4+ Doctoral Training Partnership (DTP), a collaboration between leading UK universities and research organisations, designed to train future leaders in earth and environmental sciences.

The Arctic is experiencing rapid warming, with rates over three times the global average. Recent findings from the MOSAiC expedition have shown that blowing snow over sea ice can generate fine sea-salt aerosols, which in turn affect cloud properties and surface warming. This project aims to explore whether other impurities in Arctic snow—such as black carbon, dust, organic matter, and sulfate—can also be re-emitted as secondary emissions, potentially impacting clouds, radiation, and air quality. These processes are currently missing from climate models, including the UK Earth System Model (UKESM), leading to gaps in seasonal forecasts and long-term climate projections.

As a PhD student, you will develop a new parameterisation for snow-impurity re-emission, implement it in UKESM, and validate it using in-situ data from MOSAiC and permanent Arctic observatories. The training programme includes advanced Earth system modelling, ensemble design, machine-learning tools, and Lagrangian transport modelling. You will be based at the British Antarctic Survey and collaborate closely with experts at the University of Leeds and Exeter, gaining expertise in perturbed parameter ensembles and machine-learning model integration. A CASE placement at the Met Office will provide additional applied training, access to facilities, and professional networking opportunities.

Funding for eligible students covers home tuition fees and an annual tax-free stipend (£20,780 p.a. for 2026/27) for 3.5 years, along with a project costs budget (£9,000), conference budget (£2,000), and individual training budget (£1,000). The Met Office will cover additional expenses during placements. Applicants should have a strong background in environmental science, earth science, physics, or chemistry, and experience with climate modelling or machine learning is desirable. Eligibility for home tuition fees applies, and good English language skills are required.

Applications are open for September 2026 entry, with a deadline of 8 January 2027. For further details and to apply, visit the University of Exeter funding page. For research-specific queries, contact the lead supervisor at [email protected].

Funding details

Available

What's required

Applicants should have a strong background in environmental science, earth science, physics, or chemistry. A first or upper second class degree (or equivalent) in a relevant discipline is typically required. Experience with climate modelling, machine learning, or related computational skills is desirable. Eligibility for home tuition fees applies; international applicants may not be eligible for full funding. Good written and spoken English is required.

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