Wageningen University & Research’s Animal Sciences Group (ASG) is launching a new investment programme centred on the digital transformation of the animal sciences. The programme initiative aims to further strengthen knowledge and methods in data-driven research, data science and artificial intelligence (AI). Seven PhD tracks form the core of the programme and will be carried out jointly by Wageningen BioVeterinary Research (WBVR), Wageningen Livestock Research (WLR) and Wageningen Marine Research (WMR), in close collaboration with the graduate school WIAS and Wageningen University
The PhDs work under a single theme: “Digital Biology – Integrating Behaviour, Health and Biodiversity in Animal Science”.
The ‘Digital Biology’ programme focuses on developing and applying digital technologies (AI, sensors, modelling, data fusion) to better understand and predict the behaviour, health and biodiversity of animals.
Together, the PhD candidates strive for a better understanding of the ‘digital physiology’ of animals: how behaviour, genetic predisposition, pathogens, health and environmental stimuli jointly determine how animals function, adapt and contribute to ecosystems.
PhD: Development and implementation of AI tools for identification of correlates of disease to pathogens Understanding the virulence mechanisms of complex pathogens is still needed because these pathogens circulate in livestock and wild animal populations. Effective vaccines or intervention strategies are lacking, urging the need for new perspectives on pathogen control. Within this project these perspectives will be explored.
To predict correlates of disease against these complex pathogens, you will develop and use AI-driven tools capable of predicting protein structure and folding to assess antigenicity and immunogenicity. These predicted proteins will be experimentally validated
in vitro. Ultimately, this work will contribute to future vaccine and immunological assay development.
You will:
- Identify and implement the AI-driven tools required for the assessment of antigenicity, epitope accessibility, and immune-relevant structures
- Integrate genomic, proteomic, and structural features to generate ranked lists of candidate virulence-associated proteins.
- Initiate the development of machine-learning models capable of analysing the potential of selected antigens as potential vaccine candidate and/or diagnostic target.
You will work hereThe research is embedded within Wageningen Bioveterinary research located in Lelystad embedded with the chair
Adaptation Physiology of the animal science group , and topic resilience of animals, which is led by
Prof. Annemarie Rebel . You will be co-supervised by Dirkjan Schokker