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University of Birmingham

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PhD in AI-Enabled Prediction of UK Pollen Season Magnitude for Next-Generation Forecasting University of Birmingham in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

CASE studentship with the Met Office, with additional funding and opportunities to work directly with Met Office scientists and spend time embedded with the organisation.

Deadline

Jan 6, 2027

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Country

United Kingdom

University

University of Birmingham

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Keywords

Computer Science
Data Science
Environmental Science
Biology
Mathematics
Artificial Intelligence
Atmospheric Science
Earth Science
Statistics
ML

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About this position

New PhD opportunity in the University of Birmingham group of Francis Pope, in collaboration with the Met Office and Christian Offen (University of Birmingham School of Mathematics).

The project is titled AI-Enabled Prediction of UK Pollen Season Magnitude for Next-Generation Forecasting. It is a CASE studentship with the Met Office and includes additional funding plus the chance to work directly with Met Office scientists and spend time embedded with the organisation.

This PhD sits at the intersection of environmental science, atmospheric science, mathematics, data science, and AI / machine learning. The research aims to develop novel AI and machine-learning methods to predict pollen season magnitude months in advance and support next-generation operational pollen forecasting in the UK.

The post is being shared by Francis Pope, who invites final-year or Masters students with relevant interests to apply. The deadline is 6 January 2027.

For full details and application instructions, use the project link and follow the CENTA application guidance.

Funding details

CASE studentship with the Met Office, with additional funding and opportunities to work directly with Met Office scientists and spend time embedded with the organisation.

What's required

Suitable for final-year or Masters students. Interest in environmental science, atmospheric science, mathematics, data science, or AI is specifically highlighted. The project is interdisciplinary and involves AI and machine-learning methods for forecasting.

How to apply

Read the project information at the linked CENTA page and follow the application instructions there. Contact Francis Pope if you have questions about fit or the project. Share with eligible students who may be interested.

More information can be found here

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