Fully Funded PhD in Test-Time Adaptation & Agentic AI for Multimodal Foundation Models at Aarhus University Aarhus University in Denmark

A fully funded PhD position is available at Aarhus University, Denmark, in the Department of Electrical and Computer Engineering, focusing on Test-Time Adaptation and Agentic AI for Multimodal Foundation Models. The position is part of the A3 Lab – Adaptive & Agentic AI, and aims to develop robust machine learning systems capable of adapting at test time under real-world distribution shifts. Research will address the challenges faced by modern foundation models, such as vision–language and multimodal models, which often degrade after deployment due to changes in data, environment, sensors, or user behavior.

The project will design methods for safe and efficient adaptation of these models post-deployment, emphasizing reliability and efficiency. Key research directions include test-time adaptation, agentic decision-making mechanisms, adaptive systems for reliability monitoring, distribution shift detection, trustworthy sample selection, and lightweight model updates. The project also explores feedback-driven and reward-based adaptation, uncertainty estimation, calibration, and out-of-distribution detection. The candidate will contribute to novel algorithms, theoretical insights, and large-scale empirical evaluations, with a strong focus on reproducibility and real-world impact.

The successful candidate will join a dynamic research environment, collaborate internationally, and have opportunities to publish at leading venues such as NeurIPS, ICML, ICLR, CVPR, and ECCV. Open-source contributions and interdisciplinary collaborations are encouraged. Applicants must have a relevant Master’s degree in Electrical Engineering, Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a closely related field, with strong machine learning and/or computer vision background, solid Python programming skills, and experience with deep learning frameworks like PyTorch. Prior research experience is advantageous.

The position is fully funded, with salary and terms according to the collective agreement. The application deadline is 26 February 2026, and the preferred start date is 15 May 2026. For further information, contact Associate Professor Behzad Bozorgtabar at [email protected]. To apply, submit a statement of interest, CV, academic transcripts, diplomas, and the project description as a PDF via the application link. Aarhus University values equality and diversity and encourages all qualified candidates to apply.