The position is related to ongoing strategic initiatives in the field of Digital Aquaculture. The
candidate will be given flexibility to develop research questions around modelling fish
feeding and appetite. The candidate will be expected to take into consideration some of the
following biological parameters and technologies to advance the field. The thesis will focus on
obtaining real-time information and automated analysis on the fish through 1) cameras, 2)
sonar, 3) individual fish-tagging/telemetry. This information will be integrated with
environmental information to be able to identify some of the following: biomass, fish
movement and classified behaviours (e.g. feeding, aggression, stress), fish physiological
responses (heartbeat, gill movement). The areas of application include: Image analysis,
data analysis algorithms, machine learning, deep learning, artificial intelligence, fish behavior,
data fusion, automation.