Summary
Aarhus University, Denmark, is inviting applications for a three-year PhD fellowship in Physical AI within the Electrical and Computer Engineering programme. The successful candidate will join the Adaptive & Agentic AI (A3) Lab, focusing on developing adaptive foundation models for robotics to enable intelligent robots to understand instructions, anticipate actions, and adapt reliably to changing physical environments. The position is available from January 1, 2027, or later.
Designation
PhD Fellow/Scholarship
Key Details
| Category | Detail |
|---|---|
| Host Institution | Aarhus University, Graduate School of Technical Sciences |
| Department | Electrical and Computer Engineering |
| Research Lab | Adaptive & Agentic AI (A3) Lab |
| Supervisors | Associate Professor Behzad Bozorgtabar (main), Professor Qi Zhang (co-supervisor) |
| Duration | 3 years |
| Starting Date | January 1, 2027, or later |
Research Area
The PhD position focuses on Physical AI: Adaptive Foundation Models for Robotics. The research vision is to enable intelligent robots to understand instructions, anticipate the consequences of actions, and adapt reliably when the physical world changes.
Research Directions and Objectives:
- Vision-language-action models (VLAs): Investigating VLA models and multimodal representations that connect visual observations and language instructions to robot behaviour, including learning from demonstrations and generalisation to unfamiliar tasks, objects, or environments.
- World models and planning: Developing models that predict how the physical world responds to actions, supporting planning and learning from interaction. This may include learning from video, demonstrations, and simulation, and transferring knowledge across robot configurations.
- Adaptation and edge intelligence: Developing efficient methods for maintaining reliable behaviour under changing environments, sensing conditions, and resource constraints. Topics may include test-time and continual adaptation, uncertainty-aware decision-making, and efficient inference and model updates under latency, memory, and energy limits.
The research will emphasize new learning algorithms and rigorous evaluation using public datasets, simulation, and, where available, robotic and edge-computing platforms. The goal is to produce original research for leading machine-learning, computer-vision, and robotics venues.
Location
Adaptive & Agentic AI (A3) Lab, Department of Electrical and Computer Engineering (ECE), Faculty of Technical Sciences, Aarhus University, Finlandsgade 22, 8200 Aarhus N, Denmark.
Eligibility and Qualifications
Essential Qualifications:
- A master’s degree (120 ECTS or equivalent), completed by enrolment, in computer science, electrical or computer engineering, robotics, machine learning, or a related field.
- Strong academic results and foundations in machine learning, linear algebra, probability, and optimisation.
- Strong Python and PyTorch (or comparable framework) skills.
- Substantial hands-on experience implementing, training, and evaluating deep-learning models.
- Evidence of research potential through a substantial thesis, research project, code contribution, or publication, clearly identifying personal technical contribution.
Desirable Experience:
- Research experience in multimodal foundation models or robot learning, especially involving vision–language–action models or world models.
- Experience in model adaptation or efficient edge deployment.
- Prior publications and hands-on robotics experience are advantageous but not required.
Scholarship Description
The PhD fellowship is a three-year position at Aarhus University, Denmark. The successful candidate will receive a salary and terms of employment in accordance with applicable collective agreements. The position offers an opportunity to conduct high-quality, original research in an international and interdisciplinary environment, targeting publications at top-tier conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL, RSS, and ICRA.
How to Apply
Applicants must submit their application online via the provided link. The application should include:
- A one-page statement of interest identifying relevant research directions and your strongest technical project.
- A CV with a project portfolio and publications (if applicable).
- Bachelor’s and Master’s transcripts and diplomas (as available).
- Links or an accessible description of relevant code, methods, and results, explaining your personal contribution.
- A project description: For technical reasons, applicants must upload the project description provided in the announcement as a PDF. A separate research proposal is not required.
Shortlisted applicants should be prepared for a technical interview to discuss their implementation, experimental design, results, and limitations. Clear scientific communication in English and a commitment to reproducible research are essential.
Contacts for further information:
- Main Supervisor: Behzad Bozorgtabar, behzad@ece.au.dk
- Co-supervisor: Qi Zhang, qz@ece.au.dk
- For application requirements: admission.gradschool.tech@au.dk
Last Date for Apply
November 1, 2026, at 23:59 CET.
