Assistant Professor in Statistics and Social Data Science

10 Apr 2026
Job Information

Organisation/Company

Utrecht University

Research Field

Sociology » Socio-economic research

Researcher Profile

Leading Researcher (R4)
Established Researcher (R3)

Application Deadline

17 May 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

Offer Description

We are looking for an Assistant Professor in Statistics and Social Data Science for the department of Methods & Statistics at Utrecht University. As an Assistant Professor you are involved in teaching and research activities, and as a core member of the ODISSEI Social Data Science (SoDa) team , you play a key role in developing and applying statistical and data science methods in the social sciences.
Your job
This position consists of 60% teaching and 40% research. Until the end of 2030, with potential for extension, 30% of teaching time will be bought out by the SoDa team . As a result, the role will effectively consist of 30% teaching and 70% research - including activities carried out in the context of the SoDa team.
Ideally your research activities in methods and statistic are closely aligned with the activities and focus of the SoDa team . SoDa is a dynamic, versatile, and innovative team hosted by the department of Methods & Statistics. As part of the SoDa team, you provide a meaningful contribution to computational social science research in the Netherlands. You collaborate with other researchers to design and develop a wide range of innovative projects, for example involving causal inference, machine learning, text analysis, or large-scale data integration. You support ODISSEI users via consultations and collaborative research, train researchers through workshops, and mentor SoDa fellows and students. You help strengthen and expand the team’s national presence by engaging with consortium partners and identifying new opportunities for collaborations with societal and academic partners. In addition, you (co-)lead national-scale applied research projects, for instance by taking a leading role on some scientific objectives of one of SoDa’s major research projects (Macroscope project, funded by NWO).
As our new colleague, you also engage in teaching in methodology, statistics and data science topics at the Department of Methodology and Statistics. Teaching activities may include undergraduate and graduate courses and workshops, thesis supervision, and curriculum development.

Where to apply

Website

https://www.academictransfer.com/en/jobs/360021/assistant-professor-in-statisti…

Requirements
Specific Requirements

Above all, we are looking for a proactive team player with outstanding communication and networking skills. The ideal candidate is a dynamic and independent researcher who works effectively in interdisciplinary teams and is adaptable to diverse ways of working and doing science. Moreover, the candidate demonstrates full ownership throughout all stages of complex research projects and has experience leading projects and supervising or mentoring others, either formally or informally. The candidate combines a strong methodological or technical background with a genuine interest in social science research and a commitment to open, reproducible, and societally relevant science.
Furthermore, the ideal candidate is someone who demonstrates the following qualities in research and teaching:
Research:

• Holds a PhD in a quantitative field (e.g., methods and statistics, data science, computational social science), or a relevant field with both a large quantitative component and a strong emphasis on social sciences.
• Proven research experience in the social sciences (e.g., psychology, economics, sociology, linguistics, demography, political science, communication science), demonstrated by high-quality publications developing or applying innovative methods within the social sciences.
• Experience in interdisciplinary collaboration, ideally bridging computational and social sciences domain.
• Advanced scientific programming skills (R/Python; and/or julia, MATLAB, or another relevant language) and version control (Git/GitHub). Ideally with experience developing (open-source) software or collaborating with research engineers for that purpose.
• Has broad/generalist knowledge on statistical modelling, with additional conceptual knowledge and/or practical experience in topics such as agent-based modelling, bayesian statistics, causal inference, data visualisation and graphical interfaces, geospatial data analysis, high-performance computing, natural language processing / text analysis, or privacy and ethical use of sensitive data.
• Has excellent level of English, both spoken and written.

Teaching:

• Experience with teaching academic courses in methodology, statistics, (applied) data science, machine learning, or computational methods.
• Has strong didactic skills and the ability to provide inspiring lectures.
• Holds a basic teaching qualification (UTQ/BKO or equivalent) or is willing to obtain such qualification at Utrecht University within two years after appointment.
• Dutch language skills are a bonus, or willingness to learn Dutch.

Additional Information
Benefits

• a job for 1 year with the prospect of a permanent employment contract following a positive evaluation;
• a working week of 32 - 40 hours and a gross monthly salary between € 4,728 and €6,433 in the case of full-time employment (salary scale 11, 12 under the Collective Labour Agreement for Dutch Universities (CAO NU);
• 8% holiday pay and 8.3% year-end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment laid down in the CAO NU, Utrecht University also offers a range of its own schemes for employees. This includes arrangements for professional development , various types of leave, and options for sports and cultural activities . You can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht University .

Selection process

As Utrecht University, we want to be a home for everyone. We value staff with diverse backgrounds, perspectives and identities, including cultural, religious or ethnic background, gender, sexual orientation, disability or age. We strive to create a safe and inclusive environment in which everyone can flourish and contribute.
Knowledge security screening can be part of the selection procedures of academic staff. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology.
To apply, please submit the following documents via the ‘Apply now’ button below:

• A 1-page cover letter describing your motivation and suitability for the position
• Your curriculum vitae, including a list of publications, and relevant experience on research, teaching, collaboration, and leadership.

Please note that international candidates that need a visa/work permit for the Netherlands require at least four months processing time after selection and acceptance. Our International Service Desk (ISD) can answer your questions about living in the Netherlands as international staff . Finding appropriate housing in or near Utrecht is your own responsibility, but the ISD may be able to advise you therewith. In case of general questions about working and living in The Netherlands, please consult the Dutch Mobility Portal.
In the second stage of the selection procedure, the short-listed candidates will be invited for an interview with the committee. The first round of interviews is planned for the fourth week of June (June 22- June 26).
Our preferred start date is September 1 or as soon as possible thereafter.

Additional comments

For more information, please contact Dr. Taymara Abreu at t.c.abreu@uu.nl .
Candidates for this vacancy will be recruited by Utrecht University.

Website for additional job details

https://www.academictransfer.com/360021/

Work Location(s)

Number of offers available

1

Company/Institute

Universiteit Utrecht

Country

Netherlands

City

Utrecht

Postal Code

3584CH

Street

Padualaan 14

Geofield

Contact

City

Utrecht

Website

http://www.uu.nl/

Street

Domplein 29

Postal Code

3512 JE

STATUS: EXPIRED

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