Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Mechanical and Production Engineering programme. The position is available from 1 September 2026 or later. You can submit your application via the link under 'how to apply'.
 

Title:
Evolutionary Learning and Collaborative Perception for General Purpose Robot AI

Research area and project description:
This PhD project is a part of the project, OPERA: Open Perception, Learning, and Decision-Making Toolbox for General Purpose (GP) Robot AI, granted by EU HORIZON.  To achieve efficient, adaptive, and trustworthy GPAI for multi-robot teams operating in unstructured and dynamic environments, this PhD project will establish a methodology that integrates heterogeneous sensing, collaborative perception, evolutionary learning, active motion planning, and fault-tolerant control within a System 1/2 GPAI framework. This approach emphasizes on adaptability, robustness, and reasoning beyond pattern recognition, ensuring safe operation under uncertainty and continual adaptation to evolving conditions. At the foundation lies heterogeneous sensor integration, where diverse sensing modalities (e.g., audio, spectral, 2D/3D imaging, tactile) are combined through adaptive fusion to overcome the limitations of individual sensors. This multimodal view enables reliable detection, localization, grasping, and assembly in complex environments. 

Beyond perception, This PhD project will: 1) focus on active and evolutionary planning and learning, ensuring that multi-robot teams can autonomously improve their collaboration strategies and maintain resilience in unforeseen scenarios;  2) develop a fault-tolerant perception framework , modelling potential sensor degradations and applying recovery strategies based on redundancy, substitution, and collaborative data exchange; and 3) Integrate evolutionary learning with deep and continual learning methods, enabling robots to address uncertainties, distribution shifts, and non-stationary conditions in perception, sensor fusion, and planning.

• Project description. For technical reasons, you must upload a project description. Please simply copy the project description above and upload it as a PDF in the application.

Qualifications and specific competences: 
The PhD student candidate should be qualified for being enrolled as a PhD student in our AU 4+4 degree structure. Please find more information on the AU 4+4 degree structure here. 

Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Department of Mechanical and Production Engineering, Katrinebjergvej 89 G-F, 8200 Aarhus N, Denmark.

Contacts:
Applicants seeking further information regarding the PhD position are invited to contact: 

• Associate Professor Xuping Zhang, xuzh@mpe.au.dk (main supervisor)

For information about application requirements and mandatory attachments, please see our application guide. If answers cannot be found there, please contact:

• admission.gradschool.tech@au.dk 

How to apply:
Please follow this link to submit your application. 

Application deadline is 14 May 2026 23:59 CEST. 

Preferred starting date is 1 September 2026.

Please note: 

• Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be taken into account.
• The programme committee may request further information or invite the applicant to attend an interview.
• Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.