PhD Studentship: Autonomous Emissions Detection through Probabilistic Decision Making

Project Title: Autonomous emissions detection through probabilistic decision making 

Supervisory Team: Adam Sobey and Rand Ismaeel

Project description

We're increasingly using autonomous vehicles for a range of operations. As we do this, the period of expected operation is increasing and the level of required autonomy will follow suit. In many of these scenarios we might not know what the optimum behaviour will be before we start the operation. So the vehicles will need to balance the time they spend improving their performance and exploiting the knowledge that they've gained. An example of this is determining which vessels are breaking legislation around emissions within UK sovereign waters. We need to be able to police these vessels and determine their levels of NOx and SOx emissions. One option is to send a drone but these have a limited range and must decide how they can act most effectively in each mission, depending on what is observed: the drone can try to examine as many vessels as possible, gather data to improve its future predictions or target those it thinks are most likely to be polluters. It will need to optimise its behaviour to maximise the number of positive tests over time, rather than looking for short term benefits. This type of scenario is prevalent in other applications, such as searching for gas leaks or mapping the seabed. This PhD will generate an approach to AI that allows it to adaptively change its performance over time, within the constraints of a low power, low compute autonomous vehicle.

Supervision will be provided by Adam Sobey in the Maritime Engineering group at the University of Southampton and Programme Director of Data Centric Engineering at The Alan Turing Institute, the UK’s national AI institute and Rand Ismaeel, in the Optoelectronics Research Centre as a Royal Academy of Engineering Research Fellow, jointly with the National Oceanography Centre. We are looking for a driven candidate with expertise in, or interest in learning about: Artificial Intelligence, Sensors, Evolutionary Computation and Autonomy. We are happy to take candidates who want to learn about these areas, but don’t yet have expertise. We’d particularly like to see candidates interested in making real world changes to reduce maritime emissions through development of world-leading fundamental approaches.

If you wish to discuss any details of the project informally, please contact Adam Sobey, Maritime Engineering Research Group, Email: ajs502@soton.ac.uk.

Entry Requirements

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

Closing date:

Applications should be received no later than 30 December 2023 for standard admissions, but later applications may be considered depending on the funds remaining in place.

Funding: For UK students, Tuition Fees and a stipend of £18,622 tax-free per annum for up to 3.5 years.

How To Apply

Apply online: Search for a Postgraduate Programme of Study (soton.ac.uk). Select programme type (Research), 2023/24, 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:

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

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

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