PhD Positions in Statistics: Next-Gen Latent Variable Models – 25 octobre 2026

Contexte

Umeå University in Sweden is inviting applications for one to two fully funded PhD positions in Statistics under the research project “Next-Generation Latent Variable Models for Social Data Science.” The doctoral opportunities are based at the Department of Statistics within the Umeå School of Business, Economics and Statistics (USBE).

The positions offer an opportunity for researchers with strong quantitative backgrounds to pursue doctoral studies in statistics while contributing to research involving latent variable models, statistical methodology, computational methods and modern machine learning. The PhD positions are fully funded for four years, with the possibility of teaching and/or consulting duties of up to 20% of working time. Where such duties are undertaken, the duration of the programme may be extended to ensure four years of graduate study.

The Department of Statistics is recruiting one to two PhD students for the research project “Next-Generation Latent Variable Models for Social Data Science,” led by PhD Gabriel Wallin.

The project focuses on statistical problems involving characteristics that cannot be directly observed from data. Examples include ability, attitudes, well-being and different dimensions of poverty.

Researchers working on the project will develop statistical theory, methodology and computational approaches for complex data problems, with particular attention to latent variables and their connections to modern machine learning.

The research combines methodological statistics with applications involving large-scale social science data.

Missions et responsabilités

• Develop statistical theory, methodology and computational approaches for complex data problems with attention to latent variables and modern machine learning.
• Combine methodological statistics with applications involving large-scale social science data.
• Collaborate with external partners, including organisations working in digital learning and the charity sector.
• Undertake teaching and/or consulting duties for up to 20% of working time, if applicable.

Profil recherché

• Applicants are expected to hold a degree at the advanced level with a major in Statistics, or equivalent qualifications.
• Applicants must also have satisfactorily completed at least 30 ECTS credits in Mathematics or an equivalent amount of mathematical coursework.
• Strong quantitative background.
• Relevant backgrounds including Statistics, Mathematics, Computer science, or Related quantitative disciplines.
• Very good programming skills, an interest in statistical modelling and strong motivation to develop statistical methodology for societally relevant questions.
• Knowledge of statistical machine learning, particularly both theoretical and applied understanding and its implementation, is considered a particularly strong merit.

Conditions et avantages

• Fully funded for four years of doctoral studies.
• Possibility of teaching and/or consulting duties of up to 20% of working time, with a corresponding extension to guarantee four years of graduate study.
• Anticipated starting date is 1 January 2027, or another date by agreement (latest starting date is 1 September 2027).
• International applicants requiring a residence permit must review Swedish immigration requirements.

Dossier de candidature

• A letter of application explaining the applicant’s motivation, research interests and their relevance to the position.
• A Curriculum Vitae (CV).
• The “New PhD” form provided by Umeå University.
• Copies of undergraduate and graduate theses.
• Copies of relevant degree certificates and other supporting documentation.
• Names and contact details, including email addresses, for at least two referees.

Comment postuler

Interested candidates should submit their applications through the Umeå University recruitment system no later than 4 November 2026. The official vacancy is associated with Registration Number AN 2026/1048.

For further information about the position, applicants can contact PhD Gabriel Wallin or Professor Marie Eriksson, Director of Doctoral Studies, using the contact details provided in the official vacancy announcement.