Publisher
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University of Maastricht

Just Landed

PhD Candidate in Network Modelling for Food Safety and Regulatory Decision-Making Maastricht University in Netherlands

Degree Level

PhD

Field of study

Computer Science

Funding

This is a full-time 1.0 FTE salaried PhD employment contract at Maastricht University. The initial contract is 18 months, with the prospect of a 2.5-year extension based on mutual satisfaction. The gross monthly salary is €3,204–€4,051 for 38 hours per week, with an 8% holiday allowance, an 8.3% year-end bonus, 29 vacation days plus four additional days off, possible additional compensation-hours leave, home-office allowance, pension through ABP, and other employee benefits.

Deadline

Nov 18, 2026

Country flag

Country

Netherlands

University

University of Maastricht

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Keywords

Computer Science
Mathematics
Nutrition
Food Safety
Exposure Assessment
Salud Pública
Regulatory Science
Computational Modelling
Statistics
Network Modelling

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About this position

Maastricht University is recruiting a full-time PhD candidate in network modelling for food safety and regulatory decision-making, in collaboration with Sciensano, Belgium’s public-health research organisation.

The project develops new multi-layer network modelling approaches for heterogeneous and relational food-safety data. Research will address model specification, estimation, validation, interpretation, uncertainty assessment, and robustness analysis, with applications to contaminants, consumption patterns, exposure assessment, monitoring prioritisation, risk assessment, and regulatory decision-making.

The candidate will conduct original methodological research, implement computational methods in reproducible workflows, publish in international peer-reviewed journals, present at conferences, and complete a doctoral dissertation. The project combines quantitative and computational research at Maastricht University’s School of Business and Economics with Sciensano’s expertise in food safety, contaminant risk analysis, exposure assessment, and evidence generation for public authorities.

Applicants should hold or be close to completing a relevant master’s degree in computer science, data science, applied mathematics, statistics, econometrics, operations research, physics, computational social science, systems science, or a related quantitative discipline. Programming experience in Python, R, Julia, or a comparable language is preferred. Background in network modelling, statistical or machine learning, probabilistic modelling, complex systems, or computational modelling is desirable. Food-safety or public-health experience is welcome but not required.

The position is a 1.0 FTE salaried appointment with an initial 18-month contract and potential 2.5-year extension. The gross monthly salary is €3,204–€4,051, plus holiday allowance, year-end bonus, leave, pension, and other benefits. The intended start date is January 2027, and the application deadline is 18 November 2026.

Apply through the Maastricht University vacancy portal with a motivation letter, CV, academic records, writing sample, relevant technical examples if available, and details of at least two academic referees.

Funding details

This is a full-time 1.0 FTE salaried PhD employment contract at Maastricht University. The initial contract is 18 months, with the prospect of a 2.5-year extension based on mutual satisfaction. The gross monthly salary is €3,204–€4,051 for 38 hours per week, with an 8% holiday allowance, an 8.3% year-end bonus, 29 vacation days plus four additional days off, possible additional compensation-hours leave, home-office allowance, pension through ABP, and other employee benefits.

What's required

Applicants must have a completed or near-completed master’s degree in a relevant field such as computer science, data science, applied mathematics, statistics, econometrics, operations research, physics, computational social science, systems science, or a related quantitative discipline. Demonstrated programming experience for data analysis or computational modelling is expected, preferably in Python, R, Julia, or a comparable language. Candidates should have a foundation in network modelling, statistical learning, machine learning, probabilistic modelling, complex systems, or computational modelling; an interest in structured, relational, and heterogeneous data; strong analytical and independent-working skills; and the ability to formulate methodologically and practically relevant research questions. Strong written and spoken English is required, preferably at C1 level or higher under the CEFR. Candidates must be willing to work interdisciplinarily with methodological, food-safety, public-health, and regulatory experts. Experience in food safety, contaminant risk assessment, exposure assessment, nutrition, toxicology, public health, or regulatory science is welcome but not required. Applications must include a motivation letter, CV, transcripts or course-and-grade list, a writing sample, programming/modelling/data-analysis examples if available, and contact details for at least two academic referees.

How to apply

Submit a motivation letter, CV, transcripts or course-and-grade list, writing sample, programming/modelling examples if available, and contact details for at least two academic referees through the vacancy page. Applications are due by 18 November 2026.

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