Postdoctoral position in Cyber Vulnerability Risk Modelling; FTE

Organisation/Company Tilburg University Research Field Computer science › Cybernetics Computer science › Programming Researcher Profile Recognised Researcher (R2) Final date to receive applications 29 Mar 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure?

No

Tilburg School of Humanities and Digital Sciences has a vacancy for apostdoctoral researcher in data-driven modelling of cyber vulnerability risk within the defence domain (1.0 FTE). The Center for Cognitive Science & Artificial Intelligence in the Department of Intelligent Systems at Tilburg University, in collaboration with the Faculty of Military Sciences and the Joint Sigint Cyber Unit, invites applications for a fully funded postdoctoral position focusing on predictive modelling of cyber risks.

Description
The Department of Intelligent Systems at Tilburg University, together with partners within the Ministry of Defence, invites applications for a postdoctoral position in the interdisciplinary field of cyber risk modelling and prediction. The project is conducted in close collaboration with the Faculty of Military Sciences and the Joint Sigint Cyber Unit, and is embedded within the broader research activities of the Data Science Center of Excellence of the Ministry of Defence.

The central objective of this research is to investigate how data-driven and predictive model can be developed to quantify, model and predict the risk posed by sets of cyber vulnerabilities. The project addresses both conceptual and technical challenges, including the definition of cyber vulnerability risk, the identification of predictive features, and the construction and validation of statistical or machine-learning-based models.

The postdoctoral researcher will be responsible for:

• Developing astandardized and operationalizable definition of cyber vulnerability risk;
• Identifying and operationalizing relevant variables and features that predict cyber risk;
• Constructing and curating datasets of historical cyber incidents, vulnerabilities, and associated risk indicators;
• Developing, validating and evaluating a predictive demo model(e.g. regression-based or hybrid statistical/ML approaches);
• Translating results into academic publications, technical documentation, and an evaluative final report.

The project aims to produce a validated predictive model that can support cyber risk detection and assessment within defence contexts, while also contributing to the academic literature on cyber security analytics.

• A PhD degree in data science, computer science, artificial intelligence, operations research, econometrics, or a closely related field;
• Demonstrable experience with statistical modelling, regression analysis, or predictive analytics;
• Strong programming skills and practical experience with data-driven research;
• Affinity with or experience in cyber security, cyber risk analysis, or defence-related research is highly desirable;
• Excellent command of English and strong academic writing skills;
• Ability to work in an interdisciplinary and security-sensitive research environment.

Tilburg University offers excellent benefits in a pleasant working environment:

• A full-time position (1.0 FTE)
• Dutch citizen, fluency in Dutch, excellent command of English
• The selected candidate will receive a contract for 24 months.
• A salary ranging from a minimum of 3.546 to a maximum of 5.538 gross per month for full time employment, based on UFO profile Researcher 4 and salary scale 10 of the Collective Labour Agreement for Dutch Universities.
• A holiday allowance of 8% and an end-of-year bonus of 8.3% (annually).
• Over 8 weeks of vacation leave.
• Hybrid working with home working allowance (€2 p/day) and internet allowance (€25 p/month).
• Reimbursement sustainable commuting: walking, cycling, and public transport.
• Options model for additional leave, pension, a bicycle or personal training.
• Assistance in finding accommodation (for foreign employees).
• Pension…