The goal of the PhD project is to provide an in-depth comparative investigation of the migratory phenotype in songbird species with focus on behavioural adaptations, cognitive traits and physiology. Fundamental differences in the migratory program include diel activity schedules, the use of natural sensory cues for orientation and navigation, and the exchange of information with conspecifics. The outcome of the project will fill critical gaps in animal migration theory, clarifying which role inherited information, learning, and sociality, play in shaping the phenotypic variation of migratory strategies present in songbirds.

The project includes behavioural studies of captive migratory songbirds in a state-of-the-art experimental facility with computer-controlled cues manipulation to simulate virtual landscapes and a multi-sensory array system to monitor and reveal unique characteristics of the behavioural phenotype of target species. The experimental work entails extracting behavioural information from video and audio datasets developing modern artificial intelligence algorithms. In addition, there will be opportunities to contribute to implement sensors calibration and human-machine interface software for a novel custom battery-powered data acquisition platform for studying animal orientation in the field.

This is a highly cross-disciplinary project in tight collaboration with the Faculty of Mathematics, LTH at Lund University and it is part of the LU Profile Area: Natural and Artificial Cognition (NAC) and the eSSENCE national research programme for e-Science and advanced digital technology. Cooperation with tech companies is to be expected. The project is suitable for candidates with a strong technical background and an interest in computational biology, animal behaviour and migration. Third-cycle courses will be offered to broaden the competence to include both biology and technical sciences.

Deadline for application is 15 April 2024.

For full details and how to apply, please visit the announcement in LU Varbi.