Funding providers: VisiFish Ltd. and Swansea University's Faculty of Science and Engineering
Subject areas: Behavioural Genomics, Machine Vision, Behavioural Genomics
Project start date:
- 1 October 2022 (Enrolment open from mid-September)
Aligned programme of study: PhD in Biological Sciences
Mode of study: Full-time
Fish welfare is central for the sustainable growth of aquaculture but, because fish domestication is very recent compared to mammals and birds, knowledge and protocols for assessing welfare in aquaculture is limited. Changes in behaviour (aggression) and reduction in brain size are common effects of fish farming but their importance for fish welfare are unknown. Smaller brain size and lower cognitive abilities seem related to the less complex farming environment compared to natural fish habitats. The ballan wrasse (Labrus bergylta) and the lumpfish (Cyclopterus lumpus) are currently used as cleanerfish (a biological alternative for parasite control) in the Atlantic salmon (Atlantic salmon) farming industry. These species do not coexist in the wild but are reared together in salmon cages, raising concerns about their health and welfare, but also potentially creating a more complex, richer environment than in mono-culture.
These is a collaborative PhD project that aim to improve the welfare and delousing efficacy of cleaner fish used in salmon farming. We aim to assess the behavioural and physical/genomic changes occurring in the brain of cleaner fish, to establish physiological and stress-related consequences of cohabitation under poly-culture and use the finding to improve fish welfare and inform the artificial selection of better, more efficient elite lines of cleanear fish. We will use a combination of behavioural assays and machine vision and deep-learning algorithms developed by one of the commercial sponsors (Visfish) to develop and optimise tools to assess and improve the welfare of cleanerfish in an industrial environment (SSC).
The project will focus on the following areas:
1. Baseline testing of the effect of fish interactions on behavior, brain morphology and gene expression at the facilities in CSAR
2. Tool development to assess, maintain and optimise cleanerfish welfare through machine learning (PhD 1)
3. Validation in industry
The projects are best suited for students interested on behavioural studies combined with AI and deep learning. Close collaboration with a second project on geneomics is expected and training will be provided both by the academic supervisors and the industrial partners.
Candidates must normally hold an undergraduate degree at 2.1 level in Biosciences or a related subject, or a master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).
English Language requirements: If applicable – IELTS 6.5 overall (with at least 6.0 in each individual component) or Swansea recognised equivalent.
Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.