PhD in Methodology & Statistics: Dynamic Mixture Modeling for Intensive Longitudinal Data
Tilburg University is advertising a
PhD position in Methodology & Statistics
within the Tilburg School of Social and Behavioral Sciences. The project is titled
Dynamic Mixture Modeling for Intensive Longitudinal Data
and is linked to the
Tilburg Experience Sampling Center (TESC)
.
This PhD focuses on the development of innovative
statistical methods
for
intensive longitudinal data
, including
experience sampling data
. Research themes include
dynamic mixture modeling
,
latent Markov models
, personalized prediction, adaptive measurement, evolving latent structures, and implementation of new methods in statistical software. The project combines methodological innovation with substantive applications in psychological, behavioral, and social science research.
The successful candidate will work in the Department of Methodology and Statistics and contribute to literature reviews, methodological development, empirical data analysis, software development, scientific writing, conference presentations, dissertation work, Open Science, Team Science, and some teaching/supervision duties.
Eligibility highlights:
applicants should have a completed or nearly completed research master’s degree in statistics, psychometrics, quantitative psychology, methodology and statistics, machine learning, econometrics, computational social science, data science, or a related quantitative field. Strong programming skills (e.g., R, Python, Stan), quantitative research skills, English proficiency, and interest in intensive longitudinal/experience sampling research are expected. Experience with latent-variable modeling, mixture modeling, or adaptive/personalized measurement is an advantage.
Funding and terms:
this is a full-time PhD appointment (1.0 fte) with a gross monthly salary of €3,059–€3,881, initially for 12 months with a possible extension of 36 months. The package includes vacation pay, year-end bonus, leave, home office allowance, commuting reimbursement, internet allowance, pension, and training opportunities.
Application deadline:
2026-07-06. Applications must be submitted online. The application should include a motivation letter, CV, transcript or course list, and an academic writing sample. The expected start date is 1 September 2026.
Supervision:
Dr. Leonie Vogelsmeier, Dr. Mihai Constantin, and Prof. Dr. Jeroen Vermunt.
