Identifica comportamientos de águila real aplicando técnicas de machine learning ~

19 de octubre de 2022

Identifica comportamientos de águila real aplicando técnicas de machine learning

Oferta compartida por Cristina

Movement and behavioural ecology of juvenile golden eagles


Golden eagles (Aquila chrysaetos) are among the most charismatic birds of the alpine environment. Yet due to their high mobility and their remote occurrence, large aspects of their lives remain elusive. Tagging juvenile golden eagles with the newest generation of GPS and tri-axial accelerometer (ACC) tags allows us to bring together individual space use, habitat characteristics and specific behaviours.

Research aims

The present MSc project will investigate the behaviours of juvenile golden eagles across space and time and asses their drivers and potential consequences.


The candidate will apply a ground-truthed machine learning algorithm for identifying golden eagle behaviours onto an extensive database of accelerometer-data of ca. 80 juvenile golden eagles. This will allow assessing the abundance and composition of specific behaviours in space and time. Relating these to different intrinsic and environmental factors, as well as individual performance, will allow to infer about proximate and ultimate drivers and consequences of these behaviours. The results of this thesis shall be published in a high-quality scientific journal. The project will be embedded in an ongoing PhD-project (ETHZ/Swiss Ornithological institute) and a multinational Alpine golden eagle project led by Max-Planck Institute for Animal Behaviour. The MSc thesis will not involve any fieldwork. However, visiting the study area and potentially joining a golden eagle tagging event may be possible.


Background in biology, environmental sciences, geographical sciences or similar. Strong interest in investigating ecological questions. Experience with R statistical language. Interest in learning and applying machine learning methods, working with large datasets and the analysis of movement data. Very good knowledge of English language and scientific writing. Knowledge of bird and raptor biology will be an advantage.


Dr. Matthias Tschumi
Swiss Ornithological Institute, 6204 Sempach
Tel: + 41 41 462 99 24

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