PhD Stipend in Statistical Aspects of Privacy for Spatial Health Data Aalborg University in Denmark

The Center for Clinical Data Science (CLINDA) at the Department of Clinical Medicine, Faculty of Medicine, Aalborg University, offers a fully funded PhD stipend focused on statistical aspects of privacy for spatial health data. The position begins September 1, 2026, or soon thereafter, and lasts three years. This project sits at the intersection of mathematics, statistics, and public health, aiming to develop privacy-preserving methods for analyzing sensitive health data, such as disease maps and medical imaging, without compromising individual privacy.

Leveraging rich, nationwide Danish health registry data, the research will focus on spatial data where location information can reveal important patterns but also pose privacy risks. The PhD student will work on methods like differential privacy and synthetic data generation, enabling researchers to detect trends, identify hotspots, and support health decision-making while ensuring strong privacy guarantees. The project addresses the challenge of balancing data utility with privacy in complex spatial datasets, offering the opportunity to tackle mathematically demanding problems with real-world impact.

The research is conducted in close collaboration with the Department of Mathematical Sciences, Faculty of Engineering and Science, Aalborg University. The project is part of the Novo Nordisk Foundation Data Science Collaborative Programme, “Synthetic health data: ethical development and deployment via deep learning approaches (SE3D),” involving Professor Martin Bøgsted (privacy metrics), Professor Anders Krogh (generative AI workflows), and Professor Jan Trzaskowski (GDPR compliance). There will also be interaction with the Novo Nordisk Foundation Data Science Infrastructure Programme, “The National Health Data Science Sandbox,” a network of data scientists and researchers across five Danish universities.

CLINDA is a multidisciplinary center bridging clinical practice and data science, comprising three research groups: Clinical AI, Bioinformatics and Statistics, and Data Science Methods. The PhD student will join the Data Science Methods group, which specializes in privacy-preserving techniques. CLINDA includes 17 core staff and collaborates with over 20 affiliated postdocs and PhD students from other university faculties and Aalborg University Hospital.

The Department of Mathematical Sciences conducts fundamental and applied research in statistics, including spatial statistics, computational statistics, and statistical methods for life sciences and forensics. The Department of Clinical Medicine provides research-based teaching across all medical disciplines and collaborates closely with hospitals and general practice in the North Denmark Region.

Applicants must have strong qualifications in mathematics and statistics, excellent English language skills, and preferably experience with spatial statistics. An MSc degree in mathematical statistics, mathematically founded data science, mathematical economics, or similar is required. Candidates completing their MSc before the appointment date may also apply, provided they submit a supervisor statement and MSc thesis contract. Appointment is conditional on passing the MSc exam. Enrollment as a PhD student at the Doctoral School in Medicine, Biomedical Science and Technology is required. The PhD program includes 30 ECTS of courses, teaching or dissemination experience, and a 3-6 month external research stay outside Aalborg University.

Salary and employment terms follow the Danish Confederation of Professional Associations and the state (AC collective agreement). The position is fully funded for three years. Aalborg University values diversity and encourages applications from all backgrounds. The hiring process includes shortlisting and risk assessment. For questions, contact Professor Martin Bøgsted or other listed contacts.

To apply, submit your application via Aalborg University’s recruitment system, including a motivation statement, CV, diplomas, and other relevant documents. Applications must be submitted before the deadline. All applicants will be informed of their status after shortlisting.