L’essentiel de l’offre
- Poste : PhD and Postdoctoral Research Positions in AI and Robotics
- Employeur : University of Zurich (Department of Informatics and Robotics, Robotics and Perception Group)
- Lieu : Zurich, Switzerland
- Contrat : Fully funded regular employment with social benefits
- Date limite : 27 October 2026 (rolling basis)
- Niveau requis : Master’s or PhD degree in computer engineering, computer science, mechanical engineering, robotics, physics, aerodynamics, or related discipline
Contexte
The University of Zurich (UZH), through its Department of Informatics and Robotics and Perception Group, is inviting applications for multiple fully funded PhD and postdoctoral research positions in artificial intelligence (AI), robotics, computer vision, and autonomous navigation. Successful candidates will join an internationally recognised research team working on advanced technologies with applications in autonomous systems, mobile devices, accessibility, and real-world robotic navigation.
The positions offer opportunities for researchers to work with leading academics, access world-class research facilities, collaborate with international institutions, and contribute to projects addressing fundamental challenges in robotics and AI.
Missions et responsabilités
The Robotics and Perception Group is recruiting researchers for four main research areas:
- Low-Energy, Low-Latency World Models with Event Cameras and Frames : Combining event cameras, conventional cameras, and inertial sensors to improve energy efficiency and processing speed of computer vision algorithms (SLAM, object tracking, autonomous vehicles, AR/VR). Developing algorithms that exploit event cameras’ high dynamic range, minimal motion blur, microsecond temporal resolution, and low data bandwidth.
- Vision-Based Robot Learning with World Models : Exploring machine learning techniques enabling robots to navigate complex environments, adapt to new situations, and make better decisions using visual information. Investigating deep learning methods (imitation learning, reinforcement learning, differentiable simulation) to train sensorimotor policies translating visual observations directly into control commands across flying robots, legged robots, and cars in collaboration with Professor Davide Scaramuzza.
- Learning Vision-Based Navigation Without State Estimation : Developing learning-based navigation systems mapping visual observations directly to actions without relying on an explicit state-estimation module. Investigating end-to-end learning for robust navigation via multimodal fusion, imitation and reinforcement learning, sim-to-real transfer, and agile robotic platform testing in collaboration with the National University of Singapore (NUS) with annual trips to Singapore.
- Spatial AI for Indoor Navigation of Blind People : Applying robotics and AI to improve independent indoor navigation for blind and visually impaired people. Developing reliable, accessible, and privacy-aware indoor localisation and guidance systems including indoor positioning, semantic mapping, landmark recognition, personalised route planning, accessible turn-by-turn instructions, and multimodal interaction in collaboration with other UZH laboratories.
Profil recherché
- Master’s or PhD degree in computer engineering, computer science, mechanical engineering, robotics, physics, aerodynamics, or a related discipline.
- Strong interest in robotics, computer vision, mathematics, programming, and abstract problem-solving.
- Very strong programming skills in C++ and Python.
- Excellent written and spoken English.
- Substantial experience with robotic systems and/or aerial robots.
- Background knowledge in one or more relevant fields, including deep learning, reinforcement learning, control, path planning, aerodynamics, state estimation, computer vision, or numerical optimisation.
- Additional requirements for postdoctoral applicants: excellent research record with publications in high-impact conferences or journals, and demonstrated theoretical and practical experience solving complex robotics or computer vision problems efficiently.
- Experience with ROS, PyTorch, TensorFlow, OpenCV, and Git is desirable.
Conditions et avantages
- Fully funded positions with competitive salaries.
- Regular employment with social benefits, including a pension plan and accident insurance.
- Access to advanced research infrastructure, including a large motion-capture arena, GPU computing facilities, 3D printing equipment, and electronic and mechanical workshops.
- International collaborations, academic seminars, visits from leading scientists and industry experts, and a supportive research environment with laboratory retreats, social gatherings, hikes, and ski trips.
Dossier de candidature
- Online application form submitted through the official website (PhD application form or postdoctoral application form).
- Support letters are not required at the initial application stage (can be uploaded if available; requested if selected for an in-person interview).
- Applications sent directly by email will not be considered.
Comment postuler
Procédure : Applications must be submitted through the appropriate online application form for the position sought on the University of Zurich Robotics and Perception Group website. Applications sent directly by email will not be considered.
Adresse/Lien : Visit the official University of Zurich Robotics and Perception Group website to access the application forms.
Date limite : 27 October 2026. Applications are reviewed on a rolling basis until all positions are filled; candidates are encouraged to apply as early as possible.
Contact : For questions, contact Professor Davide Scaramuzza through the group’s designated careers email address: careersrpg (AT) ifi (DOT) uzh (DOT) ch. Do not email asking whether your CV is suitable.
