Location
London

Hours
Full Time

Salary
Negotiable

About the Role
The Research Fellow is responsible for the scientific integrity and institutional memory of the SUEWS model during a period of substantial technical change. The role involves establishing evidence that the model is correct by expanding benchmarking from a single reference site to multiple sites spanning contrasting climates, defining pass criteria, and consolidating model assumptions and their validity in one place for the first time. The postholder will capture undocumented reasoning through structured interviews with the model's developers and long-standing users, documenting why particular parameterisations were chosen, what was tried and abandoned, and how the science was conducted. This material will form the training and onboarding pathway for new contributors to the project. The postholder will work closely with the Principal Investigator and the Research Software Engineer at Reading, and is expected to publish findings and present internationally.

About Us
The UCL Department of Risk and Disaster Reduction (RDR) inspires innovation and evidence-based practice focused on improving disaster risk reduction (DRR) through research, education, and partnerships. The department leads multidisciplinary research, knowledge exchange, and teaching in risk and disaster reduction and humanitarian action, aiming to provide leadership both in the UK and internationally. With 30 academic and teaching staff, 12 research staff, and 9 professional services staff, the RDR operates within the Faculty of Mathematics and Physical Sciences but collaborates across all UCL faculties and contributes to UCL’s Grand Challenges. The department runs PhD, MRes, MSc, and undergraduate programmes with a diverse international intake and engages in high-impact knowledge exchange, including reports used by government bodies and partnerships with NGOs and intergovernmental organizations. Regular public engagement events such as the Annual Conference and Humanitarian Summit are also hosted by the RDR.

What We Offer
In addition to the exciting opportunities this role presents, we offer a comprehensive benefits package including 41 days holiday (27 days annual leave, 8 bank holidays, and 6 closure days per annum), an additional 5 days' annual leave purchase scheme, a defined benefit career average revalued earnings pension scheme (CARE), cycle to work scheme, season ticket loan, immigration loan, relocation scheme for certain posts, on-site gym, enhanced maternity, paternity and adoption pay, employee assistance programme, and discounted medical insurance.

Experience
PhD in a discipline relevant to urban climate, environmental modelling, or scientific computing. Proven ability to work confidently with observational data and model output. Track record of publishing research. Experience working with scientific code and data is essential.

About You
Ability to discern correct results from incorrect ones is valued over the volume of code written. Comfortable using AI coding assistants. Excellent written communication skills for diverse audiences, from model developers to local authority users. Skilled at eliciting and faithfully recording knowledge from experienced colleagues. Open to candidates from diverse backgrounds including architecture, public health, engineering, computing, and meteorology. This role focuses on validation, documentation, and knowledge transfer rather than core code development.

Qualifications
PhD required in a relevant field. No specific career path required; capability and expertise in urban climate modelling and related disciplines are prioritized.