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Postdoc Positions in Natural Language Processing (CPH)

Aalborg Universitet · The Technical Faculty of IT and Design, Department of Computer Science · Denmark

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The Technical Faculty of IT and Design, Department of Computer Science, Section for Copenhagen, Natural Language Processing

The Department of Computer Science at The Technical Faculty of IT and Design invites applications for

two or more postdoc positions

in the area of Natural Language Processing (NLP). The positions are open for appointments from January 1, 2027 or soon thereafter. The duration of the positions is one or two years, depending on the candidate’s qualifications and preferences.

The positions are at AAU’s Copenhagen campus, located at the waterfront in Sydhavnen.

The application deadline is Monday, November 9, 2026. Interviews are tentatively planned for December 10, 2026.

The positions are hosted within the Natural Language Processing (NLP) research group

https://aaunlp.github.io/

at AAU Copenhagen, and postdocs will work under the academic leadership of Professor Johannes Bjerva

https://bjerva.github.io/

. The NLP group is a rapidly expanding research environment with strong activities in multilingual NLP, LLM security, linguistically informed approaches to NLP, factuality in LLMs, and socially sustainable AI. The group is supported by several major national and international research grants – in 2026, we have grown to 20 researchers, including a full professor, four assistant professors, one postdoc, two research assistants, and 12 PhD students.

As a postdoc, you will join a highly collaborative, international, and ambitious research community, with access to state-of-the-art computational resources. In your role, you will have the opportunity to develop an independent research profile and compete for individual fellowships and faculty positions. The positions include the opportunity to undertake one or more research stays abroad to facilitate knowledge exchange with top research environments worldwide.

The positions are in part funded by a DFF: Sapere Aude project (“Building TRUST in Text: Linguistically Motivated Language Model Detection”)

Building TRUST in Text: Linguistically Motivated Language Model Detection - Aalborg University's Research Portal

, an NNF: Ascending Data Science Investigator project (“LM2-SEC: Linguistically Motivated Language Model Security”)

https://vbn.aau.dk/en/projects/linguistically-motivated-language-model-security/

, and an Erasmus+ project on AI-based Personal Language Learning Assistants in collaboration with VSKDansk

https://www.brondby.dk/om-kommunen/nyheder/2025/08/vskdansk-far-eu-stotte-til-udvikling-af-ai-baseret-sprogtutor

.

Your work tasks

As a postdoc, you will conduct research within the area of multilingual NLP. We are seeking postdocs with two distinct profiles within this area:

  • Postdoc 1: Security, Safety, and Privacy in Natural Language Processing and AI, with a focus on Large Language Models (LLMs), LLM-based systems, and Agentic AI
  • Postdoc 2: AI-based personal language learning assistants (1 year) and AI security (1 year).

Furthermore, there will be the possibility to gain experience as a co-supervisor for PhD students associated with these projects, and to supervise students on BSc. and MSc. levels.

The positions are embedded in an active and rapidly growing research environment, including ongoing projects on, e.g., AI security, epistemic diversity, linguistically motivated NLP, and knowledge-graph grounded factuality in LLMs. The postdocs will work both independently and collaboratively within the group and will have opportunities to engage with national and international partners. As a part of the projects funding these positions, we will host internationally recognised researchers at AAU, creating additional opportunities for collaboration and knowledge exchange.

Your competencies

We are looking for candidates motivated to make fundamental scientific contributions to multilingual NLP and AI security. Candidates should have the ambition of reaching an internationally leading level of research excellence by building their own research profile, while contributing to the research environment.

Applicants must have:

  • A relevant PhD degree (e.g., NLP, AI, ML, Security, Cryptography, or a related field) and a relevant MSc degree (e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field)
  • Strong skills in machine learning and deep learning
  • Extensive experience with modern ML and NLP methods, including experience with experimentation, and with publishing in top-tier venues (e.g. ICML, ICLR, NeurIPS, ACL, EMNLP, TACL)
  • Excellent communication skills in English

Applicants with documented experience in security, privacy, safety, or robustness will be preferred.

Qualification requirements

Appointment as postdoc requires academic qualifications at PhD level.

Who we are

According to the most recent US News and World Ranking, Aalborg University ranks 4th in Europe and 27th in the world within Best Universities for Engineering. According to a 2018 MIT report, Aalborg University is considered to have the 4th best engineering program in the world. According to the recent Times Higher Education Impact ranking, Aalborg University ranks 9th in the World for UN SDG Impact.

The Department of Computer Science at Aalborg University is highly regarded among researchers, students, and external partners because of our leading research, education, and collaboration. The department currently has more than 170 scientific staff, 20 administrative staff, and 1,100 students. Education and research are built around AAU's problem-based learning model.

The Section for Copenhagen at the department is a highly collaborative research environment, currently expanding from around 40 employees to approximately 60 over the next few years. The section includes members from research groups within NLP, AI, ML, Databases, Formal Methods, Human-Centred Computing, and others, and is uniquely characterised by an open, friendly, and supportive atmosph

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