The Umeå University PhD Scholarship 2027 is an opportunity for qualified international and domestic applicants to pursue doctoral research in statistics in Sweden. The funded position is offered through the Umeå School of Business, Economics and Statistics and focuses on developing advanced statistical methods for social data science.
The selected candidate will work on a research project titled Next-Generation Latent Variable Models for Social Data Science. This project explores statistical theory, computational methods and machine learning techniques to address complex research questions involving social data.
The doctoral position is funded for four years and may include teaching or consulting duties of up to 20% of the working time. Applicants with a strong background in statistics, mathematics, computer science or a related quantitative discipline are encouraged to apply. The application deadline is November 4, 2026, and the expected start date is January 1, 2027, or another date agreed upon with the university.
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Scholarship Details |
Information |
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Host Country |
Sweden |
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Host University |
Umeå University |
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Department |
Umeå School of Business, Economics and Statistics |
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Degree Level |
PhD |
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Research Field |
Statistics |
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Research Project |
Next-Generation Latent Variable Models for Social Data Science |
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Funding |
Fully funded doctoral position |
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Duration |
Four years |
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Workload |
Full-time |
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Additional Duties |
Teaching and consulting up to 20% |
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Expected Start Date |
January 1, 2027, or by agreement |
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Application Deadline |
November 4, 2026 |
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Eligible Applicants |
Qualified domestic and international candidates |
Umeå University is offering a doctoral research position in statistics for candidates interested in advanced statistical methodology and computational research. The project aims to develop next-generation latent variable models and explore their applications in social data science.
The successful candidate will contribute to the development of statistical theory and computational approaches for analysing complex datasets. The research will also explore connections between statistical modelling and modern machine learning techniques.
The position is designed as a full-time doctoral appointment for four years. Alongside research, the candidate may undertake teaching or consulting responsibilities of up to 20% of their working time, according to the university's arrangements.
The doctoral position provides financial and academic support for students undertaking advanced research at a Swedish university.
The main benefits include:
Four-year funding: The position provides funding for the intended four-year doctoral period, subject to the employment terms.
Full-time doctoral employment: The selected candidate will work full-time on the research project.
Research experience: The candidate will develop advanced knowledge of statistical methodology, latent variable modelling, and computational techniques.
Academic development: The position provides an opportunity to build expertise in statistics and machine learning.
Teaching experience: The doctoral researcher may participate in teaching and consulting activities for up to 20% of their working time.
International research environment: The selected candidate will conduct research in Sweden and engage with academic colleagues and relevant research communities.
As this is an employment-based doctoral position, the salary and employment conditions are governed by the university's applicable rules rather than a fixed scholarship allowance.
The doctoral project focuses on developing statistical methods for analysing complex social science data. The research will explore theoretical and computational challenges associated with latent variable models and their connections to machine learning.
The key research areas include:
Statistical theory and methodology
Latent variable modelling
Statistical machine learning
Computational statistics
Analysis of large-scale social data
Development of methods for complex research problems
Applications of statistical models to societally relevant questions
The selected doctoral researcher will work on methodological research and contribute to the project's academic objectives.
Applicants should meet the academic and technical requirements of the advertised doctoral position. The main eligibility considerations include:
Advanced academic qualification: Applicants should have a degree at the advanced level with a major in statistics or equivalent qualifications.
Mathematics background: Candidates must have completed mathematics courses equivalent to at least 30 ECTS credits.
Quantitative expertise: Applicants should have a strong foundation in statistics, mathematics, computer science or a related quantitative discipline.
Programming skills: Very good programming skills are required for the position.
Research motivation: Candidates should demonstrate a genuine interest in statistical modelling and methodological research.
Machine learning knowledge: Theoretical and applied knowledge of statistical machine learning, including practical implementation, is considered a strong merit.
Applicants should ensure that their educational background meets the formal doctoral admission requirements and that they can demonstrate the relevant mathematical and programming competencies.
Applicants should prepare all required materials before starting their application. The documents include:
Application letter explaining research interests and motivation
Updated curriculum vitae (CV)
Completed PhD application form
Copies of undergraduate and graduate theses
Academic degree certificates
Academic transcripts
Names and contact details of at least two references
The application letter should clearly explain why the applicant is interested in the project and how their academic background and technical skills relate to the research topic.
Applicants must submit their applications through the university's electronic recruitment system. Follow the steps below to prepare and submit your application.
Step 1: Review the doctoral position
Carefully read the advertised position details and confirm that your academic qualifications, mathematical background, and programming skills meet the requirements.
Step 2: Prepare your application letter
Write a clear letter describing your motivation for applying, your research interests, and your relevant academic experience. Explain how your background relates to the project on latent variable models and social data science.
Step 3: Update your academic CV
Prepare a comprehensive CV that highlights your educational qualifications, research experience, programming skills, relevant coursework, and any academic publications or projects.
Step 4: Collect the required documents
Gather your academic transcripts, degree certificates, and undergraduate or graduate theses. Complete the required application form and prepare the contact details of at least two references.
Step 5: Submit your application
Complete the online recruitment application and upload all required documents. Make sure that your application is accurate and complete before submitting it.
Step 6: Wait for the selection process
The university will assess applications according to the doctoral position's eligibility and selection requirements. Shortlisted candidates may be contacted for further information or an interview.
Important dates
| Application deadline | November 4, 2026 |
| Expected starting date | January 1, 2027, or by agreement |
| Funding duration | Four years |
The last date to apply is November 4, 2026. The expected start date is January 1, 2027, although an alternative date may be agreed upon with the university.
Applicants are encouraged to prepare their documents well in advance and submit their applications before the deadline to avoid last-minute issues.
The university will assess applicants based on their qualifications, academic achievements and suitability for the research project.
The selection process may consider:
Relevant advanced-level academic qualifications
Knowledge of statistics and mathematics
Programming and computational abilities
Understanding of statistical modelling and machine learning
Research interests and motivation
Potential to contribute to the project's research objectives
Candidates with a strong understanding of statistical machine learning and experience implementing computational methods may demonstrate particularly relevant preparation for this research position.
A doctoral position at Umeå University provides an opportunity to develop specialized research skills in statistics and computational methodology. The advertised project combines theoretical research with practical applications in social data science.
The position also offers the possibility of gaining teaching experience and participating in academic activities alongside doctoral research. For students interested in careers in statistical research, higher education, data science or computational modelling, this doctoral opportunity can provide relevant academic and professional experience.
The Umeå University PhD Scholarship 2027 offers a funded four-year doctoral research opportunity in statistics for qualified candidates interested in advanced modelling, computational methods and social data science. The project provides an opportunity to develop specialized research expertise while contributing to methodological work with potential applications in social science.
Applicants should carefully review the academic and technical requirements, prepare their application documents and submit their materials before November 4, 2026. A strong application should clearly demonstrate relevant mathematical knowledge, programming abilities and motivation for doctoral research