The FernUniversität in Hagen, Germany’s only state distance-learning university, catering to over 72,000 students, providing flexible and accessible higher education opportunities to students in diverse life situations. The university conducts extensive theoretical and applied research across its five faculties, its central research unit CATALPA, and interdisciplinary research clusters.
At CATALPA, over 60 researchers collaborate to support personalized learning using AI and adaptive systems and to understand the diversity of learners and teachers as a natural part of teaching.
To expand the team, CATALPA is now filling the position of a
at the earliest possible date.
The Junior Research Group Leader in Computational Psychometrics and Innovative Assessment Approaches is encouraged to actively take part in shaping the cluster's scientific profile and activities and will cooperate with CATALPA-members from various disciplines. This includes CATALPA´s Research Professorships in Learning Sciences, Computational Linguistics and Learning Analytics as well as the Research Group Stereotype Threat, the Junior Research Group Educational NLP and several researchers at the FernUniversität´s faculties and high-ranking cooperating institutions.
The position is offered for an initial three years, with the option of a 2-year extension following an interim evaluation. The position is full-time with a salary based on level 14 of the collective bargaining agreement for German civil service employees (TV-L). The German Academic Fixed-Term Contract Act (Wissenschaftszeitvertragsgesetz) applies.
Your tasks:
- research new approaches to assessment in education and learning, which
- link to existing work in learning analytics, educational data mining, multi-modal analytics, as well as computational psychometrics and data science.
- have a core theoretical underpinning in assessment and educational theory as well as the practical and innovative integration of assessment instruments in personalized and collaborative learning support.
- develop new theoretical approaches for assessment and integrate in educational settings for online and f2f assessment.
- integrate innovative assessment approaches with AI for personalized and contextualized assessment instruments. - build up an internationally visible, independent research group that contributes to CATALPA´s reputation and visibility e.g. by
- publishing in highly-ranked journals and conferences,
- collaborating with other CATALPA members,
- attracting additional funding, and
- advising and engaging PhD candidates.
Your profile:
- Master degree and PhD in Psychology, Learning Science or comparable
- Strong background in Data Science and Psychometrics
- Experience in Learning Technology, Technology-Based Assessment, AI and Assessment
- Ideally a strong respective publication record
- ability to conduct highly visible and high-impact research and willing to attract additional funding for your research group
- strong interest in interdisciplinary and collaborative research and open to new ideas
- ability to supervise PhD candidates
What we offer:
- The opportunity to conduct independent research in a unique environment which enables field experiments with a large and highly diverse student body
- Financial and material support for your research including a funded PhD position and further funding for materials and expenses contingent on your research proposal (for example, student assistant, technical equipment and support, etc.)
- An open, stimulating and interdisciplinary work environment where good ideas are encouraged and supported
- The opportunity to teach in the faculty nearest to your discipline
We offer you an interesting position with a great deal of independence, as well as a salary according to the collective labor agreement for German public service and a supplementary pension through the state pension agency Versorgungsanstalt des Bundes und der Länder (VBL). You will also benefit from our extensive opportunities for continuing education and professional development, wide range of occupational health services, and family-friendly policies and services.
The FernUniversität in Hagen is committed to increasing the proportion of women in research and teaching. Qualified female candidates are expressly encouraged to apply. Women with equal qualifications, abilities and professional performance will be given preferential consideration, unless there are compelling reasons for preferring an outstanding male candidate. Persons with disabilities are explicitly encouraged to apply. Part-time employment is possible.
Your application:
Please submit your application (in English or German) with the following documents by 18.07.2025 via our online portal:
- An application consisting of: (a) letter of motivation (1 page); (b) curriculum vitae; (c) list of publications; (d) link to Google Scholar/ResearchGate profile (or similar); and (e) copy of certificates;
- An outline of the concept for your research group demonstrating the link to the above-mentioned responsibilities as well as to CATALPA´s overall concept and existing groups, including a short outline for a PhD project (max. 2 pages);
- The name and contact information of two referees (position, professional address, phone number and email).
The first interviews will take place online from August 4.-8.2025. The potential second interviews are scheduled for September 1.-5.2025 in Hagen.
For more information about CATALPA please visit our website: https://fernuni.de/catalpa-en or contact Prof. Dr. Marcus Specht: marcus.specht@fernuni-hagen.de
We are committed to equal opportunities:
The FernUniversität in Hagen is committed to increasing the proportion of women in research and teaching. Qualified female applicants are strongly encouraged to apply. In cases of equal qualifications, skills, and professional achievements, preference will be given to female candidates, unless there are compelling reasons for preferring an outstanding male candidate.
Candidates with disabilities are also encouraged to apply.
FernUniversität in Hagen
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Universitätsstraße 47
58097 Hagen