The University of Reading are recruiting for the Autumn 2025 cohort for the Centre for Doctoral Training in Mathematics for Our Future Climate and has an open PhD position at the intersection of data assimilation and machine learning.
Machine Learning Approaches in Bayesian and Ensemble Data Assimilation
Probabilistic data assimilation (DA) is the process of combining models with observations to obtain the filtering distribution—the conditional probability over states given past and present observations. Due to computational limitations, typically only rough approximations of the true filter are tractable. This project proposes to use machine learning (ML) to learn new DA algorithms that better approximate the true filter, holding the potential to improve forecasts and quantify their uncertainty. This will be done using strictly proper scoring rules, skill metrics with appealing theoretical properties for this purpose.
This project will focus on learning ensemble DA algorithms for use in high-dimensional chaotic systems such as the atmosphere. Initial application will be to idealised problems, but scaling up these methods to operational weather prediction will also be explored. Theoretical issues about learnability and comparisons to other methods will also be considered.
The combination of ML with DA is an active and quickly expanding area of research. However, the learning DA algorithms is an underexplored field and has the potential to significantly improve on current DA methods used for weather and climate forecasting. The student would thus be at the frontier of high-impact DA research, working with world-leading institutions on research in DA (Reading), Earth observation (NCEO), and ML (Turing Institute).
About the MFC CDT
Are you passionate about using mathematics to tackle the pressing challenges of climate change? The EPSRC Centre for Doctoral Training in the Mathematics for our Future Climate (MFC CDT) invites you to apply for our exciting PhD programme. A dynamic and interdisciplinary PhD programme that harnesses the power of mathematics to address the urgent issues presented by climate change. Jointly run by Imperial College London, the University of Reading, and the University of Southampton, and a range of partners across business, industry, charities, and government.
The MFC CDT will train highly skilled mathematicians to become future leaders in innovative research, developing environmental prediction technologies, interpreting very large datasets relating to the Earth system, and modelling the risk associated with extreme weather and climate change.
Why Choose the MFC CDT PhD Programme?
* Innovative Research Opportunities: Engage in research focused on weather and climate modelling, data analysis, and novel mathematical approaches to environmental challenges.
* Interdisciplinary Collaboration: Work with experts from diverse fields, including climate science, atmospheric physics, and related disciplines.
* Cohort Culture: Be part of a vibrant cohort-based research environment and enhance your personal skills through a bespoke training programme.
* Tailored Internships: Gain practical experience with external partners in key sectors such as insurance, energy, water, and marine industries.
* State-of-the-Art Facilities: Access cutting-edge facilities and resources to support your research endeavours.
* Mentorship from Renowned Faculty: Benefit from guidance by experienced faculty members dedicated to your academic and professional growth.
* Fully Funded Studentships: Receive a stipend, including a London weighting, PhD fees for 4 years, and a generous allowance for research-related activities.
Join Us in Shaping the Future
Your expertise and passion for mathematics can play a pivotal role in advancing our understanding of climate change. Applications are now open to become part of a community dedicated to making a positive impact on the world. For more information and to apply, visit https://mfccdt.ac.uk/ or contact the Admissions team on Admission.CDT-MFC@reading.ac.uk .
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