PhD position on dynamic modelling of animal behaviours using machine learning, intelligent sensors and computational ethology
The laboratory of Measure, Model, Manage Bio-Responses (M3-BIORES) is a world-leading research laboratory focussing on real-time monitoring and management of animal behaviours. We work in the field of “Computational Ethology” (CE) and continuously seek to integrate developments in sensor technologies and computational analysis to automate the analysis of animal behaviour . We have developed approaches for real-time bio-response modelling that provide insight into behavioural and physiological functioning of animals in a non-invasive way, and have also translated these methods into technical solutions now on the market. We have pioneered the application of CE in the automated assessment farm animal welfare, a field known as Precision Livestock Farming (PLF) .
We believe that modern monitoring technology has the capacity to unlock new insights into how humans and animals interact and will provide animals with more productive and enjoyable lives. As such, Precision Livestock Farming aims to provide an instant warning to animal farmers when something goes wrong, enabling them to take action promptly to solve the issue. It goes beyond the categorisation of behaviours that is made possible of CE by offering tools that support zoo, farm sport, working or companion animal handlers. A core part of our research approach is working with real-time sensors for the development of dynamic models to realise new insights on animal bio-responses (behaviour, physiology, thermoregulation) linked with different disease or environmental stressors.
Our approach links underpinning science to the development of technological solutions. We have published over 350 papers on this topic, with 17 patents and 2 spin-off companies. We carry out all our research through English.
Project M3-BIORES is currently doing exciting research on computational ethology, focussing on the real-time monitoring of animal behaviours using sensors and state-of-the-art real-time algorithms. We want to understand better the animals mental state, health and welfare, and translate this knowledge in innovative ICT technologies to support farmers, zoo keepers and sports professionals. We develop novel sensor-based methods that reveal insight into problems like stereotypic behaviours, stress (chronic and acute) and design early warning/decision support systems that improve their management.
The aim of this project is to develop a methodology that can link the behaviour of animals to their management in constrained environments via the analysis of dynamic variation of sensor signals. We will work on zoo, farm and/or companion animals in the project and will develop validated parametrically efficient models that describe the dominant mechanisms behind the interesting behavioural/physiological processes. The project will be carried out in collaboration with animal ethology research groups with unique experimental animal facilities and expertise.
In the project we expect to explore a number of key questions and topics:
1. Collection of valuable data: What sensor data is important for effective real-time monitoring of animals, and how does the add value to animal management? Can the data realise multiple applications and what are they?
2. Computational methodologies: Can novel machine-learning methods outperform and/or be integrated with simple dynamic modelling, and to what extent can these approaches yield new insights into animal behaviour?
3. Model-based animal monitoring: How do we pay attention to the time-varying nature of animal systems in an automated way, and what are the potential gains (animal welfare, productivity) from adoption of adaptive real-time animal monitoring systems compared to standard approaches?
Your profile M3-BIORES are now looking for a doctoral candidate to carry out this exciting research through a four year PhD project. The project would be ideally suited to a student with a strong quantitative background in computer science, engineering, or the physical sciences who has a passion to do high level research in a very engaged and ambitious research team. Prior knowledge of machine-learning techniques is not a pre-requisite but you should possess a innovative streak and hunger to learn new methodologies. The student will work in a multi-disciplinary team including ethology, signal processing, optimization and machine learning. You will also work closely with industrial partners and will be guided towards how to realise technical solutions from the science.
Necessary • You have a recent master degree from one of the countries of the EU or the EER or Switzerland
• You must be willing to obtain a PhD degree in the field of bio-science engineering at the KU Leuven
• You are able to fluently speak, read and write in English, as communicating project results in international peer reviewed journals is a major task
Desirable • Understanding in animal biology/physiology
• Experience in multi-disciplinary collaboration
• Working knowledge of MATLAB
Contact Send a short motivation and a Curriculum Vitae including at least two references . Applications should be submitted through the online application tool. For more information and application instructions, the candidates are requested to send a CV to Prof. dr. Tomas Norton, Group of M3-BIORES (Measure, Model, Manage Bioresponses) in the Faculty of Bio-Science Engineering, Katholieke Universiteit Leuven, Belgium.