
University of Zurich (UZH) · University of Zurich (UZH)
The University of Zurich in Switzerland is inviting applications for multiple fully funded PhD and postdoctoral research positions in artificial intelligence, robotics, computer vision and autonomous navigation. The opportunities are offered through the university’s Robotics and Perception Group, which conducts research into intelligent machines capable of navigating complex environments using onboard cameras and computing systems.
The research positions provide opportunities for qualified candidates to work on advanced technologies with applications in autonomous vehicles, aerial robots, mobile devices and accessible navigation systems. Researchers will collaborate with experienced academics, contribute to innovative projects and use specialised research facilities while developing their expertise in artificial intelligence and robotics.
Applications are open to candidates with relevant academic qualifications and strong programming and research skills. The group is seeking individuals who are interested in solving challenging problems in computer vision, machine learning, robot learning and autonomous systems. International applicants are welcome.
The Robotics and Perception Group is part of the Department of Informatics at the University of Zurich. Its research focuses on fundamental challenges in robotics and computer vision, particularly how autonomous machines can interpret visual information, make decisions and navigate without depending on external infrastructure.
The available positions cover four main research areas. Applicants should review the individual projects and identify those that best match their academic background, technical skills and research interests.
This project explores how event cameras, conventional cameras and inertial sensors can be combined to improve the efficiency and speed of computer vision systems. Potential applications include simultaneous localisation and mapping, object tracking, autonomous vehicles and augmented or virtual reality devices.
Researchers will investigate algorithms that use event based visual information to improve perception in challenging lighting conditions and during fast movement.
This research area focuses on machine learning methods that enable robots to understand their surroundings, adapt through experience and navigate complex environments.
Potential approaches include imitation learning, reinforcement learning and differentiable simulation. Research platforms may include flying robots, legged robots and cars, with opportunities to investigate learning from real world experience and existing video data.
This project examines whether robots can translate visual observations directly into navigation and control actions without relying on a separate state estimation system.
Research directions include combining event camera data with conventional images, developing learning based control methods, improving adaptation between simulated and real environments, and testing navigation systems on agile robotic platforms. The project involves collaboration with the National University of Singapore, with approximately one or two trips to Singapore expected each year.
This project aims to improve independent indoor navigation for blind and visually impaired people. Researchers will develop accessible and privacy aware systems that help users navigate large buildings where satellite positioning is unavailable.
Possible topics include indoor localisation, semantic mapping, personalised route planning, accessible navigation instructions and multimodal interaction through speech, audio or haptic feedback.
Successful candidates can expect the following benefits:
• Fully funded research positions with competitive salaries.
• Regular employment with social benefits, including a pension plan and accident insurance.
• Access to advanced computing infrastructure, including GPU resources.
• Access to specialised robotics facilities, motion capture equipment, 3D printing and electronic and mechanical workshops.
• Opportunities to collaborate with researchers at international institutions.
• Participation in academic seminars and research discussions with scientists and industry experts.
• Opportunities to contribute to research with practical applications in autonomous systems, accessibility and intelligent navigation.
• A collaborative academic environment with research group activities and professional development opportunities.
The announcement does not specify exact salary figures. Candidates should consult the official recruitment page for further information about compensation and employment arrangements.
Applicants should have a master’s or PhD degree in computer science, computer engineering, mechanical engineering, robotics, physics, aerodynamics or a closely related discipline.
Candidates are expected to demonstrate the following:
• Strong interest in robotics, computer vision, mathematics, programming and analytical problem solving.
• Very strong programming skills in C++ and Python.
• Excellent written and spoken English.
• Substantial experience with robotic systems or aerial robots.
• Knowledge of one or more relevant fields, including deep learning, reinforcement learning, control, path planning, aerodynamics, state estimation, computer vision or numerical optimisation.
• Academic and technical experience relevant to the selected research project.
Postdoctoral applicants must also demonstrate an excellent research record, including publications in respected conferences or journals, as well as theoretical and practical experience in solving complex robotics or computer vision problems.
Experience with ROS, PyTorch, TensorFlow, OpenCV and Git is desirable.
Applicants should prepare an application that clearly demonstrates their qualifications and suitability for the relevant research position.
Recommended materials include:
• An up to date academic CV.
• Details of educational qualifications and relevant research experience.
• Evidence of programming proficiency in C++ and Python.
• Information about previous robotics, computer vision or machine learning projects.
• Publications and research contributions, particularly for postdoctoral applicants.
• A clear explanation of research interests and their connection to the selected project.
• Any supporting letters already available. These are optional at the initial application stage.
Candidates should emphasise relevant technical achievements and explain how their skills could contribute to the research group. Postdoctoral applicants should pay particular attention to their publication records and evidence of independent research.
University of Zurich (UZH)
University of Zurich (UZH)
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