Senior Research Associate â MARS / IceDice
- Lancaster University
- United Kingdom, ENG
- Jun 28, 2026
Job Description:
Senior Research Associate – MARS / IceDice
The School of Mathematical Sciences at Lancaster University is seeking to appoint a Senior Research Associate (SRA) to work within ‘MARS: Mathematics for AI in Real-world Systems’, contributing to the NERC-funded project ‘IceDice: Predicting the stochastic behaviour of West Antarctica’s Marine Ice Sheet’.
About the role
The IceDice project aims to provide reliable probabilistic forecasts of the West Antarctic Ice Sheet’s contribution to future sea level rise – information of enormous societal and economic value for coastal planning and climate adaptation worldwide.
Your research will develop and apply novel Bayesian machine learning methods – in particular physics-informed Gaussian processes and/or neural operators– to build accurate probability density functions (PDFs) of future Antarctic sea level contributions.
Working as part of a collaborative team spanning British Antarctic Survey and the University of Cambridge, you will be based at Lancaster and work with Dr Henry Moss to:
- Develop machine learning emulators for the WAVI ice-sheet model to serve as efficient surrogates for large-scale Bayesian inference.
- Develop utility-function-based experimental design methods to identify the computer simulations and observational surveys that maximise information about future sea level for a given computational cost.
- Work closely with ice-sheet modellers at the British Antarctic Survey to apply probabilistic methods to realistic West Antarctic domains.
- Publish high-quality research in leading peer-reviewed journals and present at national and international conferences.
What we’re looking for
- PhD in statistics, machine learning, physics or a closely related discipline.
- Research experience in Bayesian methods, probabilistic modelling, or scientific machine learning.
- Experience with Gaussian processes, MCMC methods, or uncertainty quantification for expensive computational simulators.
- An interest in applying mathematical methods to real-world environmental challenges, and willingness to collaborate across disciplinary boundaries.
- Experience with Python, or equivalent scientific computing languages.
The IceDice project connects you to a world-leading collaborative team at the British Antarctic Survey and the University of Cambridge, with opportunities to engage with high-profile climate science and policy impact.
Candidates who are considering making an application are strongly encouraged to contact Dr Henry Moss ([email protected]) to discuss the role.
This is a full-time, fixed-term position for 22 months or until 31/08/2028 (whichever comes first). Flexible working arrangements will be considered, but you will be expected to be present on the Lancaster campus a minimum of two days per week.
Closing Date: 26 Jul 2026
Department: Research
Salary: £39,906 to £46,049 (Full time, indefinite with end date)
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Job Description:
Senior Research Associate – MARS / IceDice
The School of Mathematical Sciences at Lancaster University is seeking to appoint a Senior Research Associate (SRA) to work within ‘MARS: Mathematics for AI in Real-world Systems’, contributing to the NERC-funded project ‘IceDice: Predicting the stochastic behaviour of West Antarctica’s Marine Ice Sheet’.
About the role
The IceDice project aims to provide reliable probabilistic forecasts of the West Antarctic Ice Sheet’s contribution to future sea level rise – information of enormous societal and economic value for coastal planning and climate adaptation worldwide.
Your research will develop and apply novel Bayesian machine learning methods – in particular physics-informed Gaussian processes and/or neural operators– to build accurate probability density functions (PDFs) of future Antarctic sea level contributions.
Working as part of a collaborative team spanning British Antarctic Survey and the University of Cambridge, you will be based at Lancaster and work with Dr Henry Moss to:
- Develop machine learning emulators for the WAVI ice-sheet model to serve as efficient surrogates for large-scale Bayesian inference.
- Develop utility-function-based experimental design methods to identify the computer simulations and observational surveys that maximise information about future sea level for a given computational cost.
- Work closely with ice-sheet modellers at the British Antarctic Survey to apply probabilistic methods to realistic West Antarctic domains.
- Publish high-quality research in leading peer-reviewed journals and present at national and international conferences.
What we’re looking for
- PhD in statistics, machine learning, physics or a closely related discipline.
- Research experience in Bayesian methods, probabilistic modelling, or scientific machine learning.
- Experience with Gaussian processes, MCMC methods, or uncertainty quantification for expensive computational simulators.
- An interest in applying mathematical methods to real-world environmental challenges, and willingness to collaborate across disciplinary boundaries.
- Experience with Python, or equivalent scientific computing languages.
The IceDice project connects you to a world-leading collaborative team at the British Antarctic Survey and the University of Cambridge, with opportunities to engage with high-profile climate science and policy impact.
Candidates who are considering making an application are strongly encouraged to contact Dr Henry Moss ([email protected]) to discuss the role.
This is a full-time, fixed-term position for 22 months or until 31/08/2028 (whichever comes first). Flexible working arrangements will be considered, but you will be expected to be present on the Lancaster campus a minimum of two days per week.
Closing Date: 26 Jul 2026
Department: Research
Salary: £39,906 to £46,049 (Full time, indefinite with end date)
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