Wageningen University & Research
The mission of Wageningen University & Research is "To explore the potential of nature to improve the quality of life". Within Wageningen University & Research, nine specialised research institutes from the Wageningen Research Foundation and Wageningen University have joined forces to help answer the most important questions in the domain of healthy food and living environment.
With approximately 30 locations, 6,000 employees, and 12,000 students, Wageningen University & Research is one of the leading organisations in its domain worldwide. An integrated approach to problems and the cooperation between various disciplines are at the heart of the unique approach of Wageningen.
For further information about working at Wageningen University & Research, take a look at
thespecial career site.
The Department of Animal Sciences is involved in research and education related to the health and welfare of animals and people. The primary focus is on the functioning of animals, both from a curiosity-driven and an applied perspective.
The Adaptation Physiology group is part of the department of Animal Sciences. The group has expertise in immunology, reproduction, energy metabolism, behavioural physiology, and advanced analyses of large and complex data sets. The group uses an interdisciplinary approach to study adaptation and resilience of farm animals exposed to environmental perturbations. The aim of the group is to facilitate and support adaptation of animals to their changing and challenging environment in order to optimize their welfare and health. Key elements in our research are related to long-term effects of early life conditions, to supporting of animals during critical transition periods (e.g. birth, weaning, onset of lactation) and to developing new (dynamic) indicators of health and resilience. The group conducts experimental animal research and wants to increase the use of sensor technology to obtain time series of behavioural and physiological data and to use advanced modern statistical methods, machine learning, computer science and model approaches to predict and assess adaptive responses and resilience in farm animals.