Postdoc Position in Education Studies – Aarhus, Denmark

    Postdoc Position in Education Studies - Aarhus, Denmark

    Postdoc in the use of predictive algorithms in public administration is available at Department of Education Studies, Aarhus University, Denmark.

    Deadline to Apply

    Aug 01, 2021 (23: 59 GMT +1)


    PositionPostdoc Position
    No. of Position(s)1
    Research Area– Education Studies
    SalaryAccording to standard norms
    WorkplaceDepartment of Education Studies,
    Aarhus University, Denmark.
    Contract Period29 month
    Starting dateOct 01, 2021


    • PhD degree or equivalent qualifications in science and technology studies, organisation studies, anthropology, sociology, ethnography or a related discipline within the humanities or social sciences.
      The postdoc is expected to:
    • Be an active collaborative partner in the research project
    • Conduct and complete an independent research project related to the project topic and in collaboration with the group
    • Publish independently and in collaboration with the DPU co-PI and research group in relevant peer-reviewed journals
    • Initiate and organise activities with the project group, affiliated students and the academic world at large (co-organise and participate in research conferences and data sprints, seminars and webinars as well as related activities)
    • Contribute to the popular dissemination of research findings.

    Responsibilities/ Job Description

    The postdoc will work in close collaboration with the project team at DPU, consisting of co-PI Helene Friis Ratner, two postdocs and one PhD student, as well as with other participants in the ADD project.

    The primary task of the postdoc will be to identify, collect and analyse empirical data about public-sector development and/or use of predictive algorithms and the ensuing organisational and/or public disputes and controversies.

    Cases could include – but are not limited to – predicting children at risk, students dropping out of their education, citizens at risk of long-term unemployment, social fraud, and predictive policing.

    The postdoc may use methods such as multi-sited ethnography, qualitative semi-structured interviews and document analysis, depending on their academic background.

    The postdoc will also participate in interdisciplinary data sprints, mapping controversies in relation to public administration’s use of predictive algorithms, across national and social media.

    The ADD project addresses the democratic issues associated with the rapidly increasing use of algorithms in all sectors of society. One frequently voiced concern is that algorithms may lead to biased and untransparent decision making, which in turn may erode the trust in key societal institutions and decision-making processes.

    The overall aim of the ADD project is to understand the processes and circumstances that give rise to controversies around algorithms, to raise public awareness of algorithms, and to promote a democratically legitimate development of algorithms in Danish society. The ADD project will also do basic computer science research on algorithmic bias and conduct a substantial number of qualitative case studies of algorithm controversies in areas such as privacy & cybersecurity, public administration, finance, health and innovation practices.

    How to Apply?

    To apply, please click APPLY ONLINE button mentioned above.

    Documents Required

    The application must outline the applicant’s motivation for applying for the position, attaching

    • A curriculum vitae
    • A teaching portfolio
    • A complete list of published works
    • Copies of degree certificates and examples of academic production (mandatory, but no more than five examples).
      Please upload this material electronically along with your application.

    About Research project

    The DPU research group of the ADD project studies the Danish public administration’s development and use of predictive algorithms, with a special interest in the relationship between ensuing data-ethical controversies and public administration responses to these. Applying a range of statistical techniques to citizen data across different public sector registers, predictive analytics typically categorise citizens with respect to their predicted future risky behaviour.

    The potentials and promises of these AI techniques are obvious: they help public administration sectors tailor and target the citizens most at risk, and maybe even prevent and intercept the risky behaviour. However, as the numerous public and political debates around predictive analytics have shown, public administration’s use of predictive analytics is fraught with data ethical dilemmas. These revolve around issues of privacy, register merging, lack of transparency, the bias inherent in such predictive algorithms, and fundamental questions about which kind of interactions we envision taking place between the state and its citizens.

    One of the main project aims is to understand the relationship between public-sector use of predictive algorithms, controversies and trust, exploring predictive algorithms as sites of struggle and competing values. Research foci relevant to the position include questions of the development of predictive algorithms, professional disputes (e.g. regarding how public servants’ discretion and judgments are transformed with algorithmic decision-support models), and investigations of how predictive algorithms in public administration become matters of public concern.


    • All interested candidates are encouraged to apply, regardless of their personal background.
    • For further information about the benefits of working at Aarhus University and in Denmark, including healthcare, paid holidays and, if relevant, maternity/paternity leave, childcare and schooling, international applicants are encouraged to visit


    Co-principal investigator
    Helene Friis Ratner
    Tel:+45 3082 6019 or

    Official advertisement

    Postdoc in the use of predictive algorithms in public administration

    Post expires at 8:59am on Monday August 2nd, 2021 (GMT+9)

    Leave a Reply

    Your email address will not be published. Required fields are marked *