PhD Position in EEG Foundation Models: Social Neuroscience and Explainable AI Technical University of Denmark in Denmark

Are you passionate about combining social neuroscience and explainable AI to understand how the brain encodes social interaction and tracks uncertainty? The Technical University of Denmark (DTU) invites applications for a fully funded PhD position in EEG Foundation Models, supported by the Independent Research Fund Denmark. The project, titled “Decoding neural signatures of social coordination and metacognition using EEG-specialized transformers,” offers a unique opportunity to work at the intersection of neuroscience, machine learning, and cognitive science.

As a PhD student, you will join the Social Interaction and Neuroscience (SINe Lab) group within the Section for Cognitive Systems at DTU Compute. The group is renowned for its interdisciplinary research on information processing in humans and computers, with a particular focus on the signals exchanged during social interactions and their potential for modeling cognitive systems. You will collaborate closely with social neuroscientists, supervised by Associate Professor Ivana Konvalinka, and machine learning experts, co-supervised by Professor Lars Kai Hansen.

Your main responsibilities will include designing and conducting interactive multi-person (hyperscanning) EEG experiments, developing and implementing EEG-specialized transformer models, testing these models on data from social interaction experiments, and creating new methods for explainability in AI. You will also present your findings at international conferences and publish in peer-reviewed journals, contributing to the advancement of both neuroscience and AI research.

DTU Compute is an internationally recognized department with over 400 employees and 10 research sections, covering digital technologies in mathematics, data science, computer science, and computer engineering. The department emphasizes ethical, human, and sustainable approaches to research, supporting health, green transition, energy supply, and life sciences. DTU offers a vibrant, inclusive, and flexible work environment, with strong support for diversity and work-life balance.

Eligibility: Applicants must hold a two-year master's degree (120 ECTS points) or an equivalent qualification. Essential skills include experience with EEG signal processing and analysis (especially hyperscanning-EEG datasets), machine learning applied to EEG data, running experiments with human participants (particularly joint action studies), strong programming skills in Python, and excellent interpersonal abilities for interdisciplinary collaboration. Admission is subject to academic approval and enrolment in a DTU PhD programme. Applications may be submitted prior to obtaining the master's degree, but candidates cannot begin before receiving it.

Funding: The position is fully funded for three years, with salary and appointment terms based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.

Application Window: The application deadline is 30 December 2025 (23:59 Danish time), with the position starting on 1 March 2026 or by mutual agreement. Applications must be submitted online via the provided link, including all required documents in English as a single PDF file (cover letter, CV, grade transcripts, diploma, and a 1-page PhD project proposal).

DTU is committed to equal opportunity and encourages applications from all qualified candidates regardless of age, gender, disability, race, religion, or ethnic background. For further information, contact Associate Professor Ivana Konvalinka at [email protected] or visit DTU Compute. International applicants can find resources on working in Denmark and at DTU, including monthly seminars on PhD relocation and startup.

Join DTU and contribute to cutting-edge research in social neuroscience and AI, helping to create a better world through technology and scientific discovery.