Postdoctoral Research Associate

Grade UE07:  £40,497 - £48,149 per annum

CSE/School of Mathematics         

Full-time: 35 hours/week

Fixed Term: 3 years, from 1 September 2025, or by mutual agreement 

We are looking to appoint a Postdoctoral Research Associate to join us in an ambitious and high-impact climate research project funded by the UK’s prestigious new Advanced Research + Invention Agency (ARIA). The PROTECT project (Probabilistic Forecasting of Climate Tipping Points) brings together cutting-edge AI, statistical, and machine learning techniques with climate modelling, aiming to transform our understanding and prediction of climate tipping points.

We welcome candidates with expertise in climate modelling, ideally including experience with General Circulation Models (GCMs), Earth System Models, or related simulation tools. Additional knowledge of statistical methods, Monte Carlo techniques, or ensemble approaches is highly valued.

The post is advertised as full-time. We are open to hybrid working arrangements (on a non-contractual basis), combining on-campus and remote work.

The Opportunity:

The successful applicant will join a cross-disciplinary team working at the interface of climate science, statistical methodology, and computational modelling. The PROTECT project is part of the ARIA-funded programme on climate tipping points and aims to improve the scientific and statistical foundations of ensemble-based forecasting in climate models, mostly in general circulation models (GCMs).

You will work with the PI of the project (Prof. Victor Elvira) and collaborate with other ARIA projects. You will contribute to the following areas:

• Review and benchmark datasets used for initialization, calibration, and validation of GCMs, identifying sources of uncertainty and quantifying their impact.
• Work closely with ARIA collaborators to select appropriate GCMs or Earth System Models (e.g., CESM2, MPI-ESM, NEMO), with a focus on models relevant to AMOC and the North Atlantic.
• Develop and implement probabilistic ensemble techniques to improve uncertainty representation in climate simulations.
• Apply and validate Monte Carlo methods (e.g., importance sampling and other rare-event estimation methods) for the detection and probabilistic characterization of climate tipping points.
• Coordinate with other ARIA teams to ensure compatibility and reproducibility of methods, particularly within a shared definition and detection framework for tipping points.
• Contribute to the design of scalable and interpretable forecasting strategies for large climate simulators, integrating adaptive sampling and Bayesian techniques.
• Disseminate results in peer-reviewed publications and contribute to open-source codebases and documentation.
• Participate in the integration and delivery of a final modular framework for uncertainty-aware probabilistic forecasting, with the potential for policy relevance.

Applicants should have (or be close to obtaining) a PhD in climate science, climate modelling, geophysical fluid dynamics, or a closely related field. Experience with uncertainty-aware simulation or familiarity with statistical tools is desirable but not strictly required. Strong candidates from physical climate modelling will be seriously considered.

Your skills and attributes for success: 

• Experience with climate simulation models. Ideally, experience includes running general circulation models (GCMs), Earth system models, or similar simulation tools. However, training opportunities (e.g., via NCAS) are available for motivated candidates.
• Interest in probabilistic methods, ensemble simulations, or uncertainty quantification; experience is appreciated
• Ability to engage with interdisciplinary teams involving statisticians, computer scientists, and climate experts
• Programming experience in a scientific computing language (e.g., Python, Fortran, MATLAB)
• Excellent communication skills, both written and oral

Click to view a copy of the full job description (opens new browser tab) 

Application Information:

Applicants should upload a CV and a brief research statement (max two pages) when applying for the post online. In addition, they should arrange for at least two letters of reference to be sent direct to references@maths.ed.ac.uk quoting the reference number 12608 in advance of the closing date. For informal enquiries please contact Prof Victor Elvira: victor.elvira@ed.ac.uk.

As a valued member of our team you can expect:

• A competitive salary.
• An exciting, positive, creative, challenging and rewarding place to work. 
• To be part of a diverse and vibrant international community.
• Comprehensive Staff Benefits, such as a generous holiday entitlement, competitive pension schemes, staff discounts, and family-friendly initiatives. Check out the full list on our staff benefits page (opens in a new tab) and use our reward calculator to discover the total value of your pay and benefits. 

Championing equality, diversity and inclusion

The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality. 

Prior to any employment commencing with the University you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages (opens new browser tab).

The University is able to sponsor the employment of international workers in this role.  If successful, an international applicant requiring sponsorship to work in the UK will need to satisfy the UK Home Office’s English Language requirements and apply for and secure a Skilled Worker Visa.  

Key dates to note:

The closing date for applications is 4 July 2025 

Unless stated otherwise the closing time for applications is 11:59pm GMT. If you are applying outside the UK the closing time on our adverts automatically adjusts to your browsers local time zone. 

 Interviews will be held in the week starting from 14 July in an online manner.

As a world-leading research-intensive University, we are here to address tomorrow’s greatest challenges. Between now and 2030 we will do that with a values-led approach to teaching, research and innovation, and through the strength of our relationships, both locally and globally.