PhD Opportunity: Non-invasive tools to assess fish welfare and disease susceptibility under farming conditions

The student will be involved in WP2 and WP5 of the IGNITION project dealing with animal welfare assessment, novel non-invasive tools and machine learning approaches. Although aquaculture represents the fastest-growing food production sector globally, its sustainability is at stake due to the predicted effects of climate change that are not only a future but also a present reality. Adapting to the predicted changes in the short-term while taking mitigation measures in the long-term could be the only way towards sustaining the sector’s production. Therefore, new knowledge on how farmed animals cope with current aquaculture practices is of utmost importance to improve management and sustainability of the sector. The identification of solid biomarker signatures for animal health and welfare will support the development of innovative prediction tools and non-invasive biosensors as a scientific breakthrough in a precision veterinary medicine context, such as animal disease susceptibility, diagnosis, and treatment response for smart farming.

The student will gain deeper insights into the welfare of farmed animals under a scenario of climate change and current farming practices, in line with the main gaps addressed by the recent SCAR-Fish and SCAR-AHW studies regarding animal welfare. Efforts will be directed to both the effects of acute and chronic stress. Fish undergoing infections episodes will also be considered.

The main objectives include: i) discover and select non-invasive biomarkers in Atlantic salmon and European seabass which will be assessed for their suitability to be integrated into a sensor device to detect disease and monitor the health of farmed animals; ii) to develop non-invasive electrochemical sensors for quantitative analysis of selected biomarkers in farm products, using single and multiplex sensor platforms; and iii) to validate biomarker protocols and sensors for prototypes validation at industrial scale.