The primary goal of this position is to push the boundaries of computer vision and robotics. The overarching mission of our newly established research lab is to develop autonomous systems that enhance hu[AD3] [MOU4] man capabilities across a wide range of impactful applications, from everyday tasks to industry and healthcare. The group’s main focus is advancing perception for robot learning, aiming to create systems that can understand their surroundings and perform a broad range of tasks.
We are particularly interested in candidates who want to explore one or more of the following research areas: multi-modal input, continual learning, and adaptive methods for task planning and execution in real-world environments with autonomous agents. You will be a vital part of the Visual Computing Section, supervised by Theodora Kontogianni. Collaboration with academic partners, locally and internationally, will be a part of the role.
Your primary tasks will be to:
Conducting research and developing 3D vision algorithms for object detection, recognition, and scene understanding to support planning and task execution in dynamic environments.
Publishing research findings in leading international conferences and journals.
Assisting in the supervision of MSc and BSc student projects in related fields.
Managing your own academic research and administrative duties, including small-scale project management to ensure various tasks meet deadlines.
Contributing innovative ideas for new research projects.
Selection Criteria
1. A two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree in mathematics, physics, computer science, electrical engineering or closely related fields with a focus on computer vision, machine learning or robotics
2. A background in computer vision, machine learning and/or robotics.
3. Prior experience in 3D vision or related fields such as 3D reconstruction
4. Proven software and debugging skills in Python and/or C++
5. Experience with learning frameworks such as PyTorch
6. Experience in Linux and development tools such as git, conda, or docker
7. Ability to manage own academic research and associated activities
8. Excellent communication skills and ability to work on interdisciplinary teams
9. Publication record is highly desired
