Umeå University
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1 month ago
PhD in Statistics: Latent Variable Models for Social Data Science Umeå University in Sweden
Degree Level
PhD
Field of study
Computer Science
Funding
The PhD position is fully funded for four years. PhD students may be appointed to teaching and/or consulting duties up to 20% of their time, which may extend the program duration to ensure four years of graduate studies. Monthly salary is mentioned, but no amount is specified.
Deadline
Nov 4, 2026
Country
Sweden
University
Umeå University
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About this position
Umeå University (Sweden) is recruiting one to two PhD students in Statistics for the research project “Next-Generation Latent Variable Models for Social Data Science” at the Umeå School of Business, Economics and Statistics (USBE), Department of Statistics.
The project focuses on statistical theory, methodology, and computational methods for complex social science data, with emphasis on latent variable models and their connections to modern machine learning. The research is motivated by applications where important constructs such as ability, attitudes, well-being, and dimensions of poverty are not directly observable and must be inferred from data. The successful candidates will also have opportunities to collaborate with external partners in digital learning and the charity sector.
This is a fully funded PhD position for four years. Students may be assigned teaching and/or consulting duties up to 20% of their time, which may extend the appointment to preserve four years of doctoral study. The starting date is January 1, 2027, or by agreement. The application deadline is 2026-11-04.
Eligibility highlights: an advanced-level degree with a major in Statistics (or equivalent), plus mathematics coursework equivalent to at least 30 ECTS credits. The department also seeks a strong quantitative background, very good programming skills, demonstrated interest in statistical modelling, and strong motivation to develop methodology for societally relevant questions. Experience in statistical machine learning is a particularly strong merit.
How to apply: submit a motivation letter, CV, the “New PhD” form, copies of undergraduate and graduate theses, degree certificates and other supporting documents, and contact details for at least two referees through the university recruitment system.
Supervision/contact information listed in the post includes PhD Gabriel Wallin and Professor Marie Eriksson at Umeå University.
Funding details
The PhD position is fully funded for four years. PhD students may be appointed to teaching and/or consulting duties up to 20% of their time, which may extend the program duration to ensure four years of graduate studies. Monthly salary is mentioned, but no amount is specified.
What's required
Applicants should have an advanced-level degree with a major in Statistics or equivalent qualifications. They must have completed Mathematics courses equivalent to at least 30 ECTS credits. Strong quantitative background in statistics, mathematics, computer science, or a related field is expected, along with very good programming skills, demonstrated interest in statistical modelling, and strong motivation to develop statistical methodology for societally relevant questions. Strong merit is demonstrated theoretical and applied knowledge in statistical machine learning, including implementation.
How to apply
Prepare a letter of application describing your research interests and relevance to the position, a CV, the New PhD form, copies of undergraduate and graduate theses, degree certificates and supporting documents, and contact details for at least two referees. Submit the application through the university recruitment system by 2026-11-04.
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ApplyKite TwinLearns as you applyMake your next move.
Prepare your application
Review drafts and confirm requirements with the university.