Robust Decision Making (RDM) Toolkit – Delivered by CCG, STEER Centre, Loughborough University
Background
While all countries face the urgent challenge of climate change, low- and middle-income countries (LMICs) encounter even greater obstacles. Launched in 2021, the UK Foreign, Commonwealth & Development Office’s (FCDO) Climate Compatible Growth (CCG) programme supports LMICs in strengthening climate action and mobilising finance to shift investment pathways. CCG develops open-source analytical tools, datasets and modelling workflows – including OSeMOSYS and CLEWs (Climate, Land, Energy and Water systems) – and creates research with local partners to support national energy and climate planning.
OSeMOSYS and CLEWs, integrated with Decision-Making under Deep Uncertainty (DMDU) techniques, help governments navigate the uncertainties inherent in long-term planning for climate, energy, power systems, and water. These approaches identify strategies that are resilient across a wide range of plausible futures, adaptive as conditions evolve, and co-created with the institutions responsible for implementing them. Previous work led by Professor Jairo Quiros-Tortos, Deputy Director of CCG and Professor of Practice – Sustainable Transitions, has established the analytical foundation for national climate finance across more than 20 countries in Latin America, the Caribbean, and Africa, including Botswana, Zambia, and South Africa, informing over $11 billion in climate finance in partnership with multilateral development banks.
Robust Decision Making (RDM) is central to this capability: a transparent way to stress-test strategies across thousands of plausible futures rather than relying on a single forecast. Under the Climate Compatible Growth (CCG) programme, and building on CCG’s deliberative-modelling best practice (Plazas-Niño et al. 2025), Professor Jairo is leading the development of an open-access, model-agnostic RDM toolkit and workflow that connects scenario generation, exploratory modelling, vulnerability discovery, and trade-off visualisation, with open Python and Jupyter components that are model-agnostic by design by coupling to any energy or CLEWs-type model through a standard interface, rather than being tied to a single modelling framework.
The initial phase delivers one practical RDM workflow, a limited set of open software tools, two worked examples, introductory teaching material, and testing, release, and documentation – designed as a reusable global public good and to support HMG (including DESNZ) and international partners in stress-testing net-zero and energy-security strategies. This Terms of Reference covers the RDM Developer, who builds the open-source RDM software tools and interfaces and delivers testing, release, and documentation.
Objective of the Assignment
To build the open-source RDM software tools and model interfaces implementing the workflow, and to deliver testing, release, and documentation, under the technical direction of the RDM Implementation Specialist and Prof. Jairo. The Developer turns the methodology into reproducible, reusable software.
Scope of Work
The consultant will be responsible for:
- Core RDM Tooling – Develop open Python and Jupyter components implementing the RDM workflow – scenario sampling and generation, batch/ensemble model runs, results storage, vulnerability discovery (e.g. PRIM / scenario discovery), robustness metrics, and trade-off visualisation that are built to be model-agnostic so the same components work regardless of the underlying energy model.
- Model Interfaces – Build a model-agnostic adapter layer with a standard input/output contract, so the workflow can drive any energy or CLEWs-type model handling inputs, parameter sweeps, and outputs.
- Automation and Reproducibility – Implement automated checks, reproducible run configuration, and version control (Git); package components for straightforward reuse by other researchers and teams.
- Testing and Quality Assurance – Write and run tests, validate outputs against the two worked examples, and resolve defects, working to the standards set by the Implementation Specialist.
- Release and Documentation – Prepare the open-source release – repository, licensing, and release notes – together with clear technical and user documentation.
Expected Deliverables
The consultant will deliver the following (timelines to be confirmed on contracting):
| Deliverable | Description | Timeline |
| Open RDM software toolkit | Python/Jupyter components implementing the RDM workflow (scenario generation, ensemble runs, scenario discovery, robustness metrics, visualisation). | [Month 2] |
| Model interfaces | A model-agnostic adapter layer with a standard input/output contract that can wrap any energy or CLEWs-type model, covering inputs, parameter sweeps, and outputs. | [Month 2] |
| Automated testing and reproducible configuration | A test suite and reproducible run configuration under version control, validated against the worked examples. | [Month 3] |
| Open-source release and documentation | Public repository with licence and release notes, plus technical and user documentation. | [Month 3] |
Coordination and Oversight
The assignment is led and delivered by the STEER Centre, Loughborough University, under the direction of Prof Jairó Quirós-Tortós, and forms part of the RDM workstream within CCG. The consultant will work closely with RDM Implementation Specialist and Prof Quirós-Tortós, participate in regular technical reviews, and coordinate with the other RDM roles (Implementation Specialist, Developer, and Capacity-Building lead) to ensure the toolkit, worked examples, and teaching materials remain aligned. Deliverables will be subject to quality-assurance review before open-source release.
Duration and Commitment
The assignment requires an estimated commitment of approximately 65 days of development, testing, release, and documentation within the current financial year (end date 31 March 2027), with start and end dates to be confirmed at contracting. The consultant is expected to be available for scheduled technical reviews and, where relevant, demonstration workshops. Flexibility to respond to iterative feedback is essential; a stretch phase (subject to further funding) may extend the work into a fuller technical package and international training pilot.
Required Qualifications and Experience
The consultant should have the following qualifications:
- Masters level qualifications in energy, computer science, engineering, data science or a related scientific or technical field
- Strong software-development experience in Python and the scientific stack (e.g. NumPy, pandas), with Jupyter and version control (Git).
- Experience building reproducible, reusable, open-source research software, including testing, packaging, and release.
- Familiarity with more than one energy systems or CLEWs-type modelling framework (e.g. OSeMOSYS, MESSAGE, TIMES, PyPSA) and with running and post-processing energy model ensembles across different frameworks.
- Strong understanding of RDM/DMDU concepts – scenario ensembles, scenario discovery (e.g. PRIM), and robustness/trade-off analysis – sufficient to implement them faithfully.
- Excellent documentation skills and the ability to work to a methodology specified by a technical lead.
Expressions of interest
You are invited to submit the following:
- A CV
- A support statement providing detailed evidence of meeting the mandatory requirements for the position
- Confirmation that you have or are able to obtain professional insurance cover
Please submit your expression of interest to Clare McGuire on C.McGuire@lboro.ac.uk by 5pm on 7 November 2026.