Integrating machine-based image analysis into the sustainable development of Scottish aquaculture (IMBASSA)
This is an exciting and unique opportunity to join a team of researchers developing and optimising automated (artificial intelligence (AI)-based) analysis of image data as applied to aquaculture developments. This PhD combines cutting edge data collection and analysis and brings together industry (MOWI, Scottish Sea Farms) and their regulators (SEPA/NatureScot) to ensure your PhD delivers impact and enables you to build your contacts across the entire sector.
You will develop:
- Practical boat-based data acquisition skills using remotely operated vehicles (ROV) and
- Data analysis (image) skills, including building, applying, and evaluating new algorithms, based on deep learning.
Your PhD will include four highly publishable areas:
- Development of standard operating procedures to optimise data capture and consistency.
- Development and evaluation of colour correction methods to enhance image analysis.
- Development of machines to identify priority marine features (i.e., maerl) and evaluate its status (living/dead) based on colour and rugosity.
- An assessment of the regulatory implications of transitioning to machine-based image interpretation.
The context of this PhD is in environmental monitoring and conservation and our partners include the fish-farm and regulatory sectors who are contributing an extra £15K to enable additional fieldwork and travel (Shetland). This PhD would suit a biologist/ecologist with an aptitude for programming or a data-scientist with an interest in ecology. This PhD will be based at SAMS, a highly supportive, well equipped, and internationally recognised research-orientated laboratory, located within a few metres of the sea. During your PhD you will be mentored by Tom Wilding (Director of Studies) and our in-house image analysis experts and co-supervisors, John Halpin and Joe Marlow via ad-hoc/weekly catch-ups with further expert input from Rachel Shucksmith (UHI-Shetland) as necessary and at least monthly. Field-work support will be provided by SAMS’ ROV technical team and you will join our industry/regulatory partners leading ROV sampling around farms in Shetland and other areas of Scotland. You’ll be joining ca 40 SAMS PhD students, including two actively developing underwater image analysis.
AI-assisted image analysis is a massive subject area and the skills you will learn will establish you as a leader in this field. Employment prospects of PhD graduates with these skills are exceptional; PhD graduates from the group have gone onto highly successful careers in academic, regulatory and industry/consultancy sectors.
Background
This PhD is about developing artificial intelligence to facilitate sustainable aquaculture in Scotland. Scottish salmon farming is profitable, generates employment but is also controversial (Scottish Government; RAIC_Report) and needs to demonstrate sustainability. This PhD is highly innovative (academically publishable) because it is part of driving positive outcomes from the adoption of AI into environmental regulation and will showcase how AI can benefit multiple stakeholders by reducing costs and enhancing transparency. This PhD builds on our existing expertise, cost-effectively bringing together hardware whilst fully exploiting our site-proximity (SAMS/UHI Shetland), existing seabed video footage (from multiple partners) and our interdisciplinary supervisory team and steering group. You will benefit from a highly supportive, superbly equipped, experienced, inclusive and informed multidisciplinary team to develop your skillset and publish in this innovative scientific frontier from multiple perspectives.
The Scottish salmon sector seeks to double its economic value by 2030, by expanding existing operations and/or licensing new areas. The detritus from salmon farms is dispersed around the fish-cages and variously impacts the seabed. The Scottish regulator SEPA and their advisors NatureScot (both partners) are required to ensure environmental sustainability of the sector. Of particular focus are priority marine features (PMFs) which are individual taxa/biotopes considered to be highly sensitive, or which provide critical ecosystem functions. Examples of PMFs include agglomerations of sensitive individuals e.g., the coralline alga maerl. Maerl is only considered a PMF where it reaches >60% coverage (living) in >5 m x 5 m area. The sector needs non-destructive, scale-appropriate methods for identifying and mapping spatial and temporal change in sensitive species, such as maerl, at existing farm-sites and/or proposed new sites.
This PhD builds on this project:
Director of Studies: Dr Thomas Wilding
Supervisory Team: Dr John Halpin, Dr Joe Marlow (SAMS), Rachel Shucksmith (UHI).
Application Deadline: Friday May 16th 2025, 17:00 BST.
Interview Date: Thursday 5th June 2025 (morning).
Course Start Date: 1st October 2025
Funding: This 3.5 year PhD studentship is fully funded by SAMS, MOWI and Scottish Sea Farms. The studentship covers Home (UK) tuition fees, a maintenance stipend and a research training grant. International applicants are also welcome to apply but please note if the successful candidate has international fee status, they will be required to pay the difference between home and international tuition fees.
How to apply:
For full project information, eligibility criteria and an application form please visit the SAMS website:
Please note that we cannot consider CVs alone. Only applications submitted on the application form available from the SAMS website by the application deadline, including the correct supporting documents and with references submitted by your referees, will be considered for this project.