UNIVERSITY OF SOUTHAMPTON

PhD Studentship, Agents, Interactions and Complexity

Location
Southampton, United Kingdom
Salary
£15,609 tax-free per annum for up to 3.5 years
Posted
20 Jan 2022
End of advertisement period
01 Apr 2022
Ref
1668922FP
Contract Type
Fixed Term
Hours
Full Time

Agents, Interactions & Complexity

Location:  Highfield Campus
Closing Date:  Friday 01 April 2022
Reference:  1668922FP

Reducing Carbon Emissions in Shipping: An Agent-Based Approach

Supervisory Team:    Enrico Gerding, Sarvapali Ramchurn, Dominic Hudson

Project description

This truly interdisciplinary project on carbon emission reduction combines techniques from artificial intelligence, game theory, transportation, shipping and optimisation. The successful applicant will be based in the Electronics and Computer Science (ECS) department at the University of Southampton, and will be part of a larger team at Southampton and collaborate with our industry partner Shell Shipping and Maritime. We are looking for an enthusiastic applicant who is keen to work across disciplines. The PhD position is fully funded. A good grade in a computer science, transportation or operation research degree (either undergraduate or at Master’s level) is required. 

Reducing carbon emissions and moving towards clean growth are key goals for the future of the maritime sector. Indeed, in their Maritime 2050 report, the UK’s Department for Transport has set the target to reduce greenhouse gas emissions from ships by at least 50% by 2050 and major shipping operators have committed to net zero by 2050. A major change is the introduction of a carbon tax, or market-based measures, which will incentivise the reduction of emissions and can also affect trades for various routes. Such measures are actively being considered by the International Maritime Organisation (IMO), the UN agency with responsibility for maritime, as it develops its new Greenhouse Gas reduction strategy for 2023. 

This aim of the project is to compare different tax incentives and policy regimes and understand, through using agent-based models and game theory, their effect at obtaining the desired emission reduction goals. To achieve this, first, the shipping problem will be modelled as an optimization problem.  This concerns optimizing the routes to minimize costs, optimal assignment of limited resources (e.g. different vessels types) to tasks (e.g. transporting oil or other cargos from and to various ports), and, in the long term, the composition of the fleet and uptake of technical energy efficiency measures that may be employed at the vessel level to reduce emissions. A second major challenge is modelling the trading patterns and profits. and how this changes when taxes are introduced. Game-theoretic approaches are used to model individual auction markets for demand and supply for transporting cargo. 

The project is part of a larger project which aims to develop a digital twin of shipping operations. The key goal is to optimise strategic decisions, such as which vessels to lease and which technologies should be used to upgrade these vessels. If successful, this will have great impact within commercial shipping, and can also inform government policy on what types of tax regimes to adopt. 

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).

Closing date: 01 April 2022.

Funding: For UK students, Tuition Fees and a stipend of £15,609 tax-free per annum for up to 3.5 years. 

How To Apply

Applications should be made online. Select programme type (Research), 2022/23, Faculty of Physical Sciences and Engineering, next page select “PhD  Computer Science (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Enrico Gerding 

Applications should include

  • Research Proposal
  • Curriculum Vitae
  • Two reference letters
  • Degree Transcripts to date

Apply online: https://www.southampton.ac.uk/courses/how-to-apply/postgraduate-applications.page

For further information please contact: feps-pgr-apply@soton.ac.uk

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