PhD Candidate in Population-Scale Network Science
Develop innovative network science methods to analyze longitudinal population-scale social networks and compare cross-country social structures.
Best for:Best for recent or upcoming MSc graduates in computer science, mathematics, physics, or computational social science with strong programming skills in Python, R, or C++ and an interest in interdisciplinary research at the intersection of network science and social sciences.
Overview
This fully funded 4-year PhD position at Leiden University focuses on advancing network science techniques to analyze large-scale, longitudinal social network data from the Dutch population. The candidate will tackle methodological challenges such as designing fast algorithms and tailored network measures for population-scale datasets. A key objective is to create novel measures of structural equivalence to interpret subgroup differences and enable cross-country comparative analyses. The PhD will be embedded in the Leiden Institute of Advanced Computer Science (LIACS) and the interdisciplinary PLANET-NL initiative, collaborating with researchers in computational social science and network science. The role also includes limited student supervision, teaching assistance, and participation in scientific organizational activities.
What you'll do
- Conduct cutting-edge research in network science to analyze large-scale, longitudinal social network data from the Dutch population.
- Develop novel measures of structural (in)equivalence to interpret subgroup differences in social network structures.
- Design fast algorithms and tailored network measures for population-scale datasets, addressing methodological challenges.
- Collaborate with the PLANET-NL inter-university research group and the Leiden Network Science group on interdisciplinary projects.
- Co-supervise BSc and MSc students in data science and network science, contributing to academic mentorship.
- Engage in minor scientific organizational activities and participate in broader research community initiatives.
- Write an article-based PhD thesis, contributing to the broader field of network science.
Requirements
Degree required: MSc in computer science or a related field (e.g., mathematics, physics, or computational social science), with demonstrated affinity for network science or complex networks/social network analysis. Exceptional candidates who will graduate in early Spring 2027 are also encouraged to apply.
Degree offered: PhD
Language: English; near-fluent conversational proficiency demonstrated through application materials.
Instruction: English
- Proven academic writing skills, demonstrated through a writing sample (e.g., MSc thesis).
- Excellent proficiency in English, including the ability to conduct near-fluent in-person conversations.
- Programming proficiency in Python, with experience in R and/or C++.
- Curiosity and openness to interdisciplinary collaboration, particularly between computer science and social sciences.
- Ability to work independently and effectively in a team.
- No formal nationality or residency restrictions mentioned.
- Applicants must have completed or be near completion of an MSc degree (graduation in early Spring 2027 is acceptable).
- No age restrictions mentioned.
Funding & terms
How to apply
Deadline: 2026-11-12
Applicants must submit an online application via the Leiden University portal. The application should include a cover letter (max 1 page), CV, a recent writing sample (e.g., MSc thesis), and contact details for at least two references. Applications will be reviewed promptly, and promising candidates may be contacted for exploratory conversations before the deadline.
- Cover letter (max 1 page)
- Academic CV
- Recent writing sample (e.g., MSc thesis)
- Names and contact details of at least two references
Contact
Prof. Dr. Frank Takes· Supervisor
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