PhD Candidate in Network Modelling for Food Safety

Maastricht University’s School of Business and Economics, in collaboration with Sciensano, is seeking a PhD candidate to conduct original methodological research in network modelling for food safety and regulatory decision-making. The successful candidate will design and evaluate multi-layer network models to analyse complex, heterogeneous data related to food contaminants, consumption patterns, and exposure assessment. This interdisciplinary project combines rigorous computational research with real-world public health applications to support policy decisions at national and European levels. The candidate is expected to publish findings in peer-reviewed journals, participate in academic conferences, and successfully complete a doctoral dissertation.

• Develop new multi-layer network modelling approaches tailored for structured food-safety data.
• Conduct research on model specification, estimation, validation, interpretation, uncertainty assessment, and robustness analysis.
• Analyze heterogeneous data related to contaminants, consumption patterns, exposure assessment, and regulatory priorities.
• Investigate how network models can effectively support contaminant risk assessment and monitoring prioritization for authorities.
• Implement robust computational methods within reproducible research workflows using languages such as Python, R, or Julia.
• Publish research findings in international peer-reviewed journals and present work at academic conferences.
• Collaborate closely with researchers across Maastricht University, Sciensano, and external policy-facing partners.
• Complete and defend a doctoral dissertation within the agreed 4-year timeframe.