PhD positions in Statistics

Organisation/Company Utrecht University Research Field Mathematics "» Statistics Sociology » Socio-economic research Researcher Profile First Stage Researcher (R1) Final date to receive applications 26 Apr 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

Help shape how Europe measures economic well-being at the local level. In this project, you will develop innovative small area estimation methods to produce high-quality composite SDG indicators, combining survey, census, and non-traditional data sources such as web and satellite data. Contribute to ground-breaking methodology with real societal impact across the EU.

Your job

The Department of Methodology and Statistics has two openings for PhD candidates.

These PhD positions are part of a large 5-year ERC Starting Grant ) funded project (Principal Investigator Angelo Moretti) titled "Small Area Estimation Methods to Monitor the Progress towards the Sustainable Development Goals at the Subnational Level in the European Union (SAESDGs-EU)".

• PhD position in small area estimation in presence of latent variables
• PhD position in small area estimation in the context of multisource data (probability and nonprobability data)

The first position will be assigned to work package 1 (part

B):
Computing composite indicators of multidimensional social indicators within the small area estimation framework.

The second position will be assigned to work package 2:
Non-traditional data sources as auxiliary variables and multisource statistics issues.

The PhD candidates will be supervised by Dr Angelo Moretti, Dr Camilla Salvatore and Prof. Peter Lugtig who are part of the world leading group of Data Quality within the Department of Methodology and Statistics. Members of the group conduct cutting-edge research on a broad range of topics, including survey design, measurement error, nonresponse, data integration, register-based statistics, mixed-mode data collection, and methodological innovations for official statistics and social science research.

The group maintains strong collaborations with national statistical institutes, international organisations, and academic partners, ensuring that its research has both scientific impact and societal relevance.

The department offers a vibrant and collaborative research environment, with regular seminars, international visitors, and active participation in international research networks. Recently, the group organised and hosted ESRA
25, the European Survey Research Association conference, which is the largest international conference in the field of survey methodology in the world. Hosting ESRA
25 further highlights the group’s leading position and strong international reputation within the global survey research community.

PhD candidates will be embedded in this dynamic research environment and will have the opportunity to engage with leading scholars in the field, present their work at international conferences, and contribute to high-impact scientific publications.

You will

• Conduct high-quality methodological research in the field of small area estimation
• Write academic articles, blog posts and statistical software
• Disseminate the research in conferences and other relevant events.
• We are looking for someone with a background in one of the following disciplines:
  Statistics, Mathematical Statistics, Mathematics, and Social Statistics
• We also welcome applications from candidates with a background in the social sciences, provided they have advanced training in methodological statistics
• You should have advanced programming skills in R or in other statistical software such as Python, or MATLAB.
• You should have a solid knowledge of statistical inference, statistical modelling
• You are able to work in a team while maintaining autonomy
• Proficiency in English (speaking, writing, reading and listening)
• You have demonstrated academic writing skills.
• Knowledge of survey sampling
• Knowledge of structural equation…