Summary
Applications are invited for a fully funded PhD scholarship in Physical AI: Adaptive Foundation Models for Robotics at Aarhus University, Denmark. This three-year position, available from January 1, 2027, focuses on developing intelligent robots that can understand instructions, anticipate actions, and adapt reliably to changing physical environments. The successful candidate will join the Adaptive & Agentic AI (A3) Lab, conducting original research for leading machine-learning, computer-vision, and robotics venues.
Designation
PhD Position in Physical AI: Adaptive Foundation Models for Robotics
Scholarship Details
| Category | Details |
|---|---|
| Qualification Type | PhD |
| Location | Aarhus, Denmark |
| Funding For | UK Students, EU Students, International Students |
| Funding Amount | Competitive |
| Hours | Full Time |
| Placed On | 23rd September 2026 |
| Closes | 1st November 2026 |
| Starting Date | 1st January 2027 or later |
Research Area
The research will focus on Physical AI, specifically developing Adaptive Foundation Models for Robotics. Key directions include:
- Vision-language-action models (VLAs): Investigating multimodal representations connecting visual observations and language instructions to robot behavior, including learning from demonstrations and generalization 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 involve learning from video, demonstrations, and simulation, and transferring knowledge across robot configurations.
- Adaptation and edge intelligence: Developing efficient methods for maintaining reliable behavior under changing environments, sensing conditions, and resource constraints, including test-time and continual adaptation, uncertainty-aware decision-making, and efficient inference under latency, memory, and energy limits.
The project emphasizes new learning algorithms and rigorous evaluation using public datasets, simulation, and robotic/edge-computing platforms, aiming for publications in top-tier conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL, RSS, and ICRA.
Location
Aarhus University, Graduate School of Technical Sciences, Department of Electrical and Computer Engineering, Aarhus, Denmark.
Eligibility/Qualification
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 optimization.
- Strong Python and PyTorch (or comparable framework) skills.
- Substantial hands-on experience implementing, training, and evaluating deep-learning models. General interest in AI or experience limited to running tutorials or using pretrained-model APIs is not sufficient.
- Evidence of research potential through a substantial thesis, research project, code contribution, or publication, clearly identifying the applicant’s own technical contribution.
Scholarship Description
This is a fully funded PhD fellowship/scholarship position within the Electrical and Computer Engineering programme at Aarhus University. The successful candidate will be supervised by Associate Professor Behzad Bozorgtabar and co-supervised by Professor Qi Zhang. The scholarship offers a competitive funding amount and is open to UK, EU, and International students, covering full-time study for three years.
How to Apply
Applicants must submit their application via the ‘Apply’ button provided on the original job posting. For technical reasons, a project description must be uploaded; applicants should copy the project description from the source and upload it as a PDF in their application. Please read the full job description on the university homepage before applying.
Last Date for Apply
1st November 2026 at 23:59 CET
