UNIVERSITY OF SOUTHAMPTON

PhD Studentship, Civil, Maritime and Environmental Engineering

Location
Southampton, United Kingdom
Salary
£15,609 tax-free per annum for up to 3.5 years
Posted
19 Jan 2022
End of advertisement period
25 Feb 2022
Ref
1667622DA
Contract Type
Fixed Term
Hours
Full Time

Civil, Maritime & Environmental Engineering

Location:  Highfield Campus
Closing Date:  Friday 25 February 2022
Reference:  1667622DA

Supervisory Team:    Adam Sobey (CMEE), Markus Brede (ECS) and Amy Parkes (Industry)

Data driven modelling of supply chain constraints in maritime transport

Project description

Recent incidents, such as the blocking of the Suez Canal or lack of workers at Chinese ports due to COVID, demonstrate the importance of maritime trade. Ships carry >90% of world trade, moving 3.5 billion tonnes of cargo (expected to triple by 2050) and 350 million passengers through 1,200 ports every year. These goods and people are carried by ~56,000 merchant ships ranging from small domestic ferries to 400m long containerships which transport 23,000 shipping containers at a time. The result of this is a complex flow network defined by port capacities, trade requirements, and routing choices of a large number of diverse ships. It is vital that we become more efficient in how we move goods around the world and that the resilience in these shipping networks is maintained and increased.

Understanding and optimising these large networks is a challenging task, due to the size and the number of follow-on effects that cascade from an initial decision. We need to simplify these networks, without loss of information, to allow clear decision making and to ensure that we understand the implications of decisions made around where to deliver goods and in what timeframe. 

In this interdisciplinary project you will develop novel tools at the boundary between complexity science, supply chain theory and maritime engineering, to explore shipping networks to optimise the behaviour of ships with an aim to enhancing resilience and reducing the complexity of the network. 

You will be supported by the Southampton Marine and Maritime Institute as part of a cohort of multi-disciplinary SMMI scholars. Supervision will be provided by Adam Sobey in the Maritime Engineering group and Markus Brede in the Agents, Interaction and Complexity groups at the University of Southampton. In addition you will work closely with the Marine and Maritime group, in the Data-Centric Engineering Programme in The Alan Turing Institute, the UK’s national AI institute. 

The project is also supported by Arcsilea, who provide bespoke consultancy to inform maritime policy on decarbonisation, with industrial supervision provided by Dr Amy Parkes. However, we want you to help us grow the network of partners through the project using early research to generate wider interest from the maritime industries and those who use shipping to transport goods. 

We are looking for a driven candidate with expertise in, or interest in learning about, Data Driven Modelling, Machine Learning, Networks, Complexity Science and Maritime transport. We’d particularly like to see candidates interested in making real world changes to reduce maritime emissions through development of world-leading fundamental approaches in complexity science.

Entry Requirements

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

Closing date: 25 February 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

Apply online https://www.southampton.ac.uk/courses/how-to-apply/postgraduate-applications.page. Select programme type (Research), 2022/23, Faculty of Physical Sciences and Engineering, next page select “PhD  Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name of the supervisor  Adam Sobey 

Applications should include

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

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

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