The National Center for AI in Society (CAISA) at the Faculty of Social Sciences, University of Copenhagen, invites applications for a two-year postdoctoral position within AI Systems Engineering. The position is part of a larger research initiative on responsible artificial intelligence in collaboration with Statistics Denmark.
The position is full-time and begins on 1 October 2026, or as soon as possible thereafter. The selected candidate will be employed at CAISA and based in Copenhagen.
CAISA, which is established as part of the Danish government's strategic initiative for artificial intelligence (AI), is an interdisciplinary national research consortium led by the University of Copenhagen in close collaboration with the Pioneer Centre of AI. The ambition is to create excellent, interdisciplinary research in a dynamic, open, and international environment with active exchange and engagement with society.
As part of CAISA's broader research agenda, including the moonshot “Responsible algorithms for all of Denmark”, the center has recently received funding from the Danish Research Reserve for a new collaborative initiative with Statistics Denmark. This initiative aims to strengthen both research in responsible artificial intelligence (AI) and the infrastructure that enables such research, including secure access to and analysis of large-scale register data.
The research activities within the project are organised around five interrelated work packages (WPs), with the postdoc joining an interdisciplinary team of 4–5 postdocs and researchers working across key dimensions of responsible AI. The present postdoctoral position is linked to a Work Package led by Associate Professor Nicki Skafte Detlefsen, DTU Compute.
The overall purpose of this postdoctoral position is to research and build the technical infrastructure that ensures responsible AI remains fair, reliable, and safe when deployed in the real world — not just under controlled laboratory conditions. Possible topics include automated pipelines for continuous bias and fairness auditing, tools for bridging cutting-edge research models and Statistics Denmark's secure infrastructure, and monitoring systems that detect model drift or performance degradation before these issues affect citizens or policy decisions. It is critical that this research addresses the practical deployment challenges of the collaboration with Statistics Denmark.
Applicants must have a PhD degree or document equivalent qualifications in one or more of the following areas: responsible AI, MLOps, AI systems engineering. Applicants are required to document:
Finally, applicants are asked to provide a proposal for research to be undertaken within the stated framework of the research project (max. 1-2 pages). Please note that although the application process can be completed on the University of Copenhagen system without uploading publications, applications that do not include uploaded research publications (max. five) will not be considered.
Terms of employment are in accordance with the Danish Confederation of Professional Associations (Akademikerne). The salary range starts at DKK 39,900 per month + a 18,07 % contribution to the pension scheme. It is possible to negotiate salary supplements on an annual basis.
The University of Copenhagen is committed in its pursuit of academic excellence to equality of opportunity and to creating an inclusive working environment and therefore encourages all qualified candidates to apply, regardless of personal background, gender, sexual orientation, age, disability, ethnicity etc.
For further information please contact Associate Professor, Nicki Skafte Detlefsen, nsde@dtu.dk, Section for Cognitive systems at Technical University of Denmark (DTU), senior researcher in CAISA.
Submit a complete application at our online portal. The documents must be in Adobe PDF or Word.
Your application must be written in English and include the following documents:
The closing date for applications is 23:59 CEST 3/08/2026. Applications or enclosures received thereafter will not be considered.
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