This PhD opportunity at The University of Manchester focuses on developing agent-based, AI-driven digital twins to support coordinated decarbonisation of global maritime transport networks. Maritime transport is a critical sector for global productivity but is also a major source of greenhouse gas (GHG) emissions. With increasing regulatory and market pressures, including UK/EU/IMO policy frameworks, the sector faces the urgent challenge of reducing lifecycle GHG emissions without compromising efficiency and reliability.

The project aims to create an agent-based digital twin model representing key decision-makers and operational constraints in real-world maritime settings, including ports, shipping companies, logistics actors, and diverse vessel types. Policy frameworks will be integrated as scenario parameters and incentive settings, such as carbon costs, emissions-intensity constraints, and fuel/infrastructure assumptions, enabling robust evaluation under realistic regulatory conditions.

Three main research questions guide the project: (1) Identifying operational strategies that combine routing, speed choice, port-call sequencing, turnaround and berth practices, and energy logistics to achieve significant emissions reductions with minimal productivity loss; (2) Understanding how limited information, misaligned incentives, and local optimisation lead to coordination failures, and how human-AI collaborative decision-making can improve system-level performance; (3) Assessing the transferability and scaling of effective strategies across regions and market segments, considering network structures and transition conditions.

A UK corridor case study (Dover–France) will serve as a demonstration and validation setting, supported by industry partners such as Port of Dover and DFDS. This collaboration will provide operational insight, validate assumptions, and illustrate practical application of decision-support strategies.

The student will join an interdisciplinary supervisory team with expertise in maritime operational research, engineering, climate science, and AI/network science. Engagement with the Centre for AI and Decision Sciences and the Tyndall Centre for Climate Change Research will offer cross-faculty training in agent-based modelling, optimisation, applied AI, and stakeholder engagement. Expected outputs include publishable research, conference presentations, and practical insights for industry and policy stakeholders.

Applicants must have a First class Bachelor's (Honours) degree or overseas equivalent and a Master's degree in a relevant subject with an average of 65% or above. Strong quantitative skills and interdisciplinary research experience are desirable, particularly in maritime systems, optimisation, simulation, data science, AI, and industry collaboration. English language proficiency is required, with minimum scores specified for IELTS, TOEFL, and PTE. Applications must include academic transcripts, certificates, CV, supporting statement, writing sample, and two academic referees. Interviews are expected in May 2026.

The President’s Doctoral Scholar Award provides full funding for tuition fees and a stipend at the UKRI rate plus a £1,000 enhancement for four years, starting in September 2026. Candidates are responsible for relocation and associated costs. The University of Manchester is committed to equality, diversity, and inclusion, and encourages applicants from all backgrounds.

For further information or questions, contact Dr Arijit De at [email protected]. More details are available on the project website.