PhD Position in Statistics

Uppsala University Department of Statistics

PhD Student in Statistics with Focus on Inference from Textual Data

Uppsala University is a comprehensive research-intensive university with a strong international standing. Our mission is to pursue top-quality research and education and to interact constructively with society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University has 46.000 students, 7.300 employees and a turnover of SEK 7.3 billion.

The Department of Statistics has about 30 employees, of which about 10 Ph.D. students. Our primary research areas are causal inference, econometrics/time series analysis, high dimensional multivariate linear models, and structural equation modeling.

The Department of Statistics is looking for a Ph.D. student in Statistics which can perform high quality methodological and statistical research within the field of statistical inference from large scale textual data.

Starting date: 1st of April 2021 or according to agreement.

The rules governing the process of enrolment as a Ph.D. student can be found (in Swedish) in Högskoleförordningen 5 kap §§1-7, and in the rules and guidelines of Uppsala University,

Duties/Project description: The position is at the Department of Statistics in collaboration with two large research projects at Linköping University and Umeå University. The aim is research in statistical method development for textual data with applications in the social sciences and the humanities. 

The position is within the projects Mining for Meaning (led by assoc. prof. Marc Keuschnigg at the Department of Analytical Sociology, Linköping Universityand Welfare State Analytics (led by prof. Pelle Snickars, Umeå University). The research will also be conducted in close collaboration with the Datalab at the Swedish National Library in Stockholm, where some work needs to be undertaken.

A Ph.D. student’s duties are primarily directed at his/her research education, which lasts four years. The work may also involve, to a limited extent (maximum 20%) other departmental duties, mainly related to teaching undergraduate courses – in which case the position may be extended to a maximum of five years. 

Local guidelines for the salary of Ph.D. students apply for employed doctoral students. 

The Ph.D. program in Statistics includes 240 credits, 90 credits of courses, and a dissertation of 150 credits. 

Requirements: For admission to the Ph.D. program in Statistics, an applicant must have basic and specific eligibility prescribed by the Faculty of Social Sciences. Anyone with a degree on the advanced level (i.e., a master’s degree) with completed course requirements of at least 240 credits (including at least 60 credits at an advanced level) has fulfilled the necessary entry requirements. The master’s degree can be in statistics, computer science, or another closely related discipline. 

The specific eligibility requirements for admission to the Ph.D. program in Statistics require that the applicant has passed 90 credits in statistics courses. Anyone that has acquired equivalent knowledge in any other way, in or out of the country, is also considered to fulfill the basic or specific eligibility requirements. Information about eligibility requirements and admission rules can be found on the web site of the University, Admissions Ordinance for Studies at the Graduate Level. The candidate should also have a good command of spoken and written English.

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines

Merits: In addition to the required qualification, experience in the following areas would be a merit for the position:

  • Experience in probabilistic modeling of textual data
  • Experience in software development in Python, Julia, and/or R
  • Strong computational and mathematical background
  • Knowledge of probabilistic programming frameworks, such as Stan or Tensorflow Probability, especially for textual data
  • Experience in interdisciplinary research collaborations, preferably in history and/or sociology

Apply via the link at the bottom of the page. A complete application must include:

  • Curriculum Vitae / Résumé
  • A brief description (1-2 pages) of research interests and relevant experience, and why you apply to the PhD program
  • Certified transcript(s) of your academic record/degree(s) to date, proving the basic and specific eligibility
  • A copy of independently written work produced within the applicant’s course of studies (e.g. bachelor or master thesis; include a draft if not completed) or other relevant text(s)
  • Academic references (with contact details)
  • Other documents the applicant may wish to attach, e.g. English test results.

Incomplete applications will not be considered.

Salary: According to local agreement for PhD students.

Starting date: 01-04-2021 or as otherwise agreed.

Type of employment: Temporary position according to the Higher Education Ordinance chapter 5 § 7.

Scope of employment: 100 %

For further information about the position please contact: Assistant Professor Måns Magnusson at the Department of Statistics, email You can also contact the head of department Ronnie Pingel, phone +46 18 471 1042, e-mail

Please submit your application by 29 January 2021, UFV-PA 2020/4631

Are you considering moving to Sweden to work at Uppsala University? If so, you will find a lot of information about working and living in Sweden at You are also welcome to contact International Faculty and Staff Services at

Please do not send offers of recruitment or advertising services.

Submit your application through Uppsala University's recruitment system.

Placement: Department of Statistics

Type of employment: Full time , Temporary position longer than 6 months

Pay: Fixed salary

Number of positions: 1

Working hours: 100 %

Town: Uppsala

County: Uppsala län

Country: Sweden

Union representative: ST/TCO
Seko Universitetsklubben

Number of reference: UFV-PA 2020/4631

Last application date: 2021-01-29

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