Introduction
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[1]. 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)[2].
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
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.
email. tomas.norton[at]kuleuven.be