Research Fellow in Modelling and Optimisation

Fixed Term Contract for 2 years

Full time starting salary is £38,655 per annum

Location: Cranfield, Bedfordshire

We welcome applications from talented and motivated researchers to join the Centre for Digital and Design Engineering at Cranfield University and contribute to the EPSRC-funded TransiT programme on Digital Twinning Technologies for Transport Decarbonisation.

About the Role

We are seeking an enthusiastic researcher to develop advanced modelling and optimisation methods that support lower-carbon, efficient, and resilient transport systems and AI-enabled circular manufacturing supply chains. Working with researchers, industry partners, and stakeholders, you will apply computational and AI-based approaches to analyse complex transport and manufacturing systems and identify improved operational, technological, and investment strategies.

The role focuses on developing optimisation and decision-support tools to evaluate operations, infrastructure, technology transitions, energy demand, costs, emissions, and resilience. Research areas may include transport and manufacturing operations, alternative fuels and technologies, infrastructure planning, resource allocation, scheduling, fleet and machine composition, and investment sequencing.

You will collaborate with teams developing simulation models, digital twins, data architectures, and federated models, providing optimisation capabilities to improve system performance. This is an opportunity to contribute to high-impact research addressing UK net-zero challenges while developing methods applicable across transport, manufacturing, energy, and other complex engineering systems.

About You

You will hold, or be close to completing, a PhD/EngD in Engineering, Operational Research, Applied Mathematics, Computer Science, Systems Engineering, Data Science, or a related field. You should have experience in optimisation, computational modelling, operational research, or quantitative decision analysis, with the ability to translate complex engineering and operational challenges into practical optimisation problems.

We welcome expertise in areas such as mathematical programming, multi-objective, stochastic or simulation-based optimisation, logistics and infrastructure planning, resource allocation, scheduling, sustainability optimisation, uncertainty analysis, and AI-supported optimisation. Strong programming and analytical skills are essential, with experience in Python, MATLAB, R, Java, or optimisation tools such as Gurobi, CPLEX, or Pyomo desirable.

You should be comfortable working with complex datasets, evaluating strategies, and communicating findings to diverse audiences. Knowledge of transport decarbonisation, energy systems, or sustainable engineering is advantageous. Strong teamwork, communication, and project management skills are essential, while experience in collaborative research and publication is desirable.

About Us

As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here.

Our Values and Commitments

Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more here.

Working Arrangements

Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners.

How to apply                                    

For an informal discussion about this opportunity, please contact Dr Maryam Farsi on maryam.farsi@cranfield.ac.uk

Please contact us for further details on peoplerecruitment@cranfield.ac.uk, quoting 5395.

Closing date:  12 October 2026

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