Research Fellow: AI-Driven Transport Modelling & Optimisation

Cranfield University; Cranfield; Hybrid; GBP 36,000 - 48,000; Full time

Benefits offered by this job

Disability Confident Employer

Flexible working options

Job summary

Cranfield University invites applications for a Researcher role in the Centre for Digital and Design Engineering. You will develop advanced modelling and optimisation methods to support decarbonisation in transport and manufacturing, working with researchers, industry partners and stakeholders.

The role focuses on computational and AI-based approaches to analyse scenarios, balance cost, carbon, resilience and performance, and contribute to evidence-based decision-making in a multidisciplinary

Qualifications

• PhD or EngD (or near completion) in Engineering, OR, Applied Mathematics, Computer Science, Systems Engineering or Data Science.
• Strong experience in optimisation, computational modelling, OR or quantitative decision analysis.

Responsibilities

• Develop advanced modelling and optimisation methods for low-carbon, efficient transport systems and AI-enabled manufacturing supply chains.
• Analyse scenarios across complex transport and manufacturing systems to identify improved operational, technological and investment strategies.
• Translate stakeholder requirements into tractable optimisation problems and evaluate alternative strategies.

Skills

Optimization

Modelling

Operational research

Data analysis

Python

MATLAB

R

Java

Pyomo

AnyLogic

Education

PhD/EngD or near completion

Tools

Python

MATLAB

R

Java

Gurobi

CPLEX

Pyomo

AnyLogic

MATSim

Simulink

Job description

Cranfield University invites applications for a Researcher role in the Centre for Digital and Design Engineering. You will develop advanced modelling and optimisation methods to support decarbonisation in transport and manufacturing, working with researchers, industry partners and stakeholders.

The role focuses on computational and AI-based approaches to analyse scenarios, balance cost, carbon, resilience and performance, and contribute to evidence-based decision-making in a multidisciplinary