PhD Candidate: Network Modelling for Food Safety & Policy

Maastricht University; Maastricht; Hybrid; EUR 36,000 - 45,000; Full time

Benefits offered by this job

Home office allowance

Flexible working hours

Job summary

Maastricht University, in collaboration with Sciensano, invites applications for a PhD candidate in Network Modelling for Food Safety and Regulatory Decision-Making. The project develops new multi-layer network models for structured food-safety data, linking methodological research with policy-facing questions and real-world regulatory impact.

The candidate will work under a supervisory team from Maastricht University and Sciensano, focusing on methodological rigor, reproducible research, and

Qualifications

• Strong quantitative and computational background.
• Completed or near-completed master’s degree in a quantitative field.
• Experience with programming for data analysis or modelling in Python, R, or Julia.

Responsibilities

• Develop new network modelling approaches for structured food-safety data.
• Specify, estimate, validate, and interpret network models for regulatory decision-making.
• Analyze heterogeneous data relevant to food safety, contaminants, exposure, and regulation.
• Investigate how network models support contaminant risk assessment and monitoring prioritisation.
• Implement computational methods in reproducible research workflows.
• Publish results in international peer-reviewed journals and present at conferences.
• Collaborate with Maastricht University and Sciensano researchers and partners.
• Complete a doctoral dissertation within the agreed timeframe.

Skills

Quantitative background

Programming for data analysis

Python

R

Mathematical modelling

CEFR English (C1)

Education

Master's degree in a relevant field

Tools

Python

R

Julia

Job description

Maastricht University, in collaboration with Sciensano, invites applications for a PhD candidate in Network Modelling for Food Safety and Regulatory Decision-Making. The project develops new multi-layer network models for structured food-safety data, linking methodological research with policy-facing questions and real-world regulatory impact.

The candidate will work under a supervisory team from Maastricht University and Sciensano, focusing on methodological rigor, reproducible research, and