PhD Researcher on Cooperation between Autonomously Controlled Robots

Job description 

IDLab is a research group of Ghent University, as well as core research group of imec. IDLab performs fundamental and applied research on data science and internet technology, and is structured in 21 research teams. The research for this position will be conducted within the DECIDE research team.

DECIDE conducts cutting-edge research on Distributed and Embodied Computing in Dynamic Environments. The team works to realize a vision where humans and robots cooperate seamlessly, enabled by advanced planning and control algorithms, real-time and energy-efficient sensing, and distributed perception. Its research is applied across diverse sectors, including agriculture, manufacturing and remote sensing.

DECIDE is currently seeking bright and highly motivated candidates to join its team. The current position is for a PhD research and education assistant (“Assistant Academic Staff”).

Research Topic

As robotic systems increasingly enter unstructured, dynamic environments—from manufacturing lines and logistics centers to hospitals and homes—the ability of multiple robots to autonomously cooperate becomes critical. Traditional multi-robot systems often rely on centralized controllers, pre-programmed sequences, or tightly synchronized schedules. However, in real-world scenarios where robots are developed by different vendors, operate under partial observability, or are dynamically added or removed from the workspace, centralized coordination becomes a bottleneck. This motivates a shift toward decentralized cooperation between autonomous robots, each with its own controller, sensors, and objectives. These individual objectives might be fully aligned, or mixed-motived.

This research aims to investigate fundamental mechanisms for real-time, task-driven cooperation between independently controlled robots. Example use cases include: (1) two stationary arms working along a moving conveyor belt, where they must pick or manipulate objects while avoiding collisions, delays, or redundant actions; and (2) a pair of mobile robots, one carrying a container and the other equipped with a manipulator, which must coordinate to transfer and store items through dynamic, spatial cooperation. These settings exemplify the challenges of distributed decision-making, perception sharing, and coordination under uncertainty.

Unlike traditional collaborative robotics, which often treats robot arms as passive tools controlled by a central planner or treats cooperation in a master-slave paradigm, we focus on peer-to-peer robotic collaboration, where each robot makes autonomous decisions while negotiating and adapting to the behavior of others. This paradigm mirrors recent trends in multi-agent reinforcement learning and  distributed AI, but focuses on high-precision tasks involving physical interaction in shared workspaces.

Role and responsibilities

In this position, you spend 50% of your time on research and 50% of your time on supporting the academic education, specifically in courses that are part of the curriculum of Master of Science in Information Engineering Technology. Conditional on a yearly positive evaluation, the fully funded position extends up to 6 years.

Your main tasks include: 
·    You will investigate and extend cooperative control mechanisms, based on state-of-the-art machine learning technologies. 
·    You will apply your work to use cases
·    Writing high quality publications, targeting top journals and international conferences.
·    You provide teaching assistance for courses in the master of Science in Information Engineering Technology, at bachelor as well as master level
·    You can take on a mentoring role by supervising bachelor and master theses related to the subject of your PhD.  

Job profile

We are looking for a highly creative and motivated PhD student with the following qualifications and skills: 
·    You have (or will obtain in the next months) a European master's degree in computer science, Artificial Intelligence, or equivalent, with excellent ('honors'-level or above) grades.
·    You have a strong background in deep learning.
·    Previous experience with robotics, reinforcement learning or other ML-based techniques for control is considered a plus.
·    You have excellent computer science skills (python, git, linux, ROS, etc.) .
·    You have hands-on experience with machine learning frameworks such as PyTorch.  
·    You have strong analytical skills to interpret the obtained research results. 
·    You are a team player and have strong communication skills. 
·    Your English is fluent (C1 CEFR level), both speaking and writing. Mastery of Dutch (both speaking and writing) is considered as a strong plus.

Our offer

We offer the opportunity to do this research in an international and stimulating environment. The research will be conducted at the premises of IDLab, located in Ghent.  

Ghent University consistently ranks among the best 100 universities in the world. Located in the heart of Europe, Ghent is a beautiful and welcoming city with plenty of cultural and leisure activities. 

The selected candidate will be offered a 6-year employment, conditional on positive outcomes of yearly intermediate evaluations. The salary is competitive and will be determined by the university salary scales. In addition, staff members can count on a number of benefits, such as a broad range of training and educational opportunities, 36 days of vacation leave, bicycle allowance, eco vouchers, and more.

How to apply

Apply through the UGent job website.

However, before formally applying, candidates are strongly encouraged to contact Prof. Pieter Simoens (pieter.simoens@ugent.be) to discuss research responsibilities, and Prof. Veerle Ongenae (Veerle.ongenae@ugent.be) to discuss teaching assistance responsibilities.

Application deadline: July 1st, 2025 (firm).