Research Fellow: AI‑Driven Modelling & Optimisation for Transport

Cranfield University; Cranfield; Hybrid; GBP 38,000 - 52,000; Full time

Job summary

Cranfield University invites applications for a researcher to develop advanced modelling and optimisation methods supporting low‑carbon, efficient and resilient transport systems. You will work with colleagues across simulation, data architectures and digital twins to analyse scenarios and recommend optimal investment and operational decisions.

The role emphasises evidence‑based decision making, collaboration with industry partners, and publication in peer‑reviewed journals.

Qualifications

• Doctorate or near completion in Engineering, Operational Research, Applied Mathematics, Computer Science, or related field.
• Experience in optimisation and computational modelling, formulating real‑world problems as tractable optimisation problems.
• Strong analytical and programming skills; familiarity with Python, MATLAB, R, Java and optimisation solvers.

Responsibilities

• Develop modelling and optimisation approaches for transport/manufacturing systems and decarbonisation.
• Translate stakeholder requirements into optimisation problems and evaluate strategies.
• Collaborate with researchers and industry partners and publish findings.

Skills

Optimisation

Computational modelling

Data analysis

Programming

Python

MATLAB

R

Pyomo

Communication

Education

PhD or EngD in Engineering/Applied Mathematics/CS

Tools

Gurobi

CPLEX

AnyLogic

MATSim

Python

MATLAB

Pyomo

Job description

Cranfield University invites applications for a researcher to develop advanced modelling and optimisation methods supporting low‑carbon, efficient and resilient transport systems. You will work with colleagues across simulation, data architectures and digital twins to analyse scenarios and recommend optimal investment and operational decisions.

The role emphasises evidence‑based decision making, collaboration with industry partners, and publication in peer‑reviewed journals.