Job Information
Organisation/Company: University of Bern
Department: Institute of Computer Science
Research Field: Computer science » Modelling tools
Researcher Profile: First Stage Researcher (R1), Recognised Researcher (R2), Established Researcher (R3)
Positions: PhD Positions
Application Deadline: 30 Sep 2026 - 00:00 (Europe/Zurich)
Country: Switzerland
Type of Contract: Temporary
Job Status: Full-time
Hours Per Week: 42
Offer Starting Date: 1 Oct 2026
Is the job funded through the EU Research Framework Programme?: Other EU programme
Is the Job related to staff position within a Research Infrastructure?: No
Offer Description
University of Bern – Computer Vision Group
Are you passionate about deep learning, self-supervised learning, generative AI, and pushing the boundaries of artificial intelligence? The Computer Vision Group (CVG) at the University of Bern, Switzerland, invites applications for two PhD positions and two postdoctoral positions across two ambitious research projects.
About the Positions
Successful candidates will conduct original research in one of the following areas:
Project 1: Collaborative World Models
1 postdoctoral position, joining two PhD researchers who have been already recruited for the project
This project investigates collaborative world-model agents: independently operating visual models that learn to predict how environments evolve, retain distinct perspectives and memories, and communicate to solve problems together. The central question is what these agents should represent and exchange, and how they can align predictions, negotiate plans, and coordinate actions while remaining autonomous and specialized. The research combines generative video modeling, self-supervised learning, memory, test-time adaptation, and decisionmaking, with potential applications in embodied AI and robotics. The successful candidate will join an existing team working on controllable, memory-augmented, and task-solving world models.
Project 2: Self-Supervised and Meta-Learning for Rapid Adaptation
2 PhD positions and 1 postdoctoral position
This project investigates how the structure of pretraining data and the choice of learning objective shape the prior knowledge acquired by deep-learning models, and how these priors can be optimized to enable rapid adaptation to novel tasks. The research combines the development of novel datasets, controlled benchmark environments, and methods for evaluating knowledge and problem-solving with the design of new learning algorithms and architectures for efficient, robust, and transferable intelligence. The project is fully funded for four years and will be carried out in close collaboration with Prof. Andrea Vedaldi at the University of Oxford.
General Information
- All positions are fully funded within their respective projects
- Start date: October 1, 2026, or by agreement
- Applications will be reviewed until excellent candidates are found
- Successful candidates will conduct original research within a well-established and dynamic research group
Your Profile
We are looking for curious and ambitious researchers who are eager to work on high-impact questions in artificial intelligence.
For PhD applicants:
- A master's degree in computer science, engineering, mathematics, or a related field, completed or expected by the starting date
- A strong interest in conducting fundamental research in machine learning and artificial intelligence
For postdoctoral applicants:
- A PhD in computer science, engineering, mathematics, or a related field, completed or expected by the starting date
- A strong research and publication record in machine learning, deep learning, computer vision, or a closely related area
- The ability to conduct independent research and contribute to the scientific guidance of junior researchers
All applicants should have:
- A solid foundation in machine learning, deep learning, and computer vision
- Strong skills in applied mathematics, probability, and programming, such as Python or C/C++
- Experience with at least one major deep-learning framework, preferably PyTorch
- The ability to work both independently and collaboratively
- Excellent communication skills and fluency in English
Experience relevant to at least one of the projects, including world models, video generation, generative modeling, self-supervised learning, meta-learning, reinforcement learning, multi-agent systems, or embodied AI, is an advantage. Applicants are not expected to have expertise in all these areas.
What We Offer
- A collaborative and innovative research environment
- A vibrant academic team and opportunities to work with world-class researchers
- Access to state-of-the-art computing infrastructure (Swiss AI large scale GPU cluster)
- Opportunities to publish at top-tier conferences and participate in the international research community
- Funding to attend international conferences, workshops, and training programs
- A competitive salary according to University of Bern regulations, with additional compensation for teaching duties
- The opportunity to live in Bern, a beautiful and highly livable city in the heart of Switzerland
Where to apply
Website: https://www.cvg.unibe.ch/vacancies/
Requirements
Research Field: Computer science » Modelling tools
Education Level: PhD or equivalent
Skills/Qualifications
We are looking for curious and ambitious researchers who are eager to work on high-impact questions in artificial intelligence.
For PhD applicants:
- A master's degree in computer science, engineering, mathematics, or a related field, completed or expected by the starting date
- A strong interest in conducting fundamental research in machine learning and artificial intelligence
For postdoctoral applicants:
- A PhD in computer science, engineering, mathematics, or a related field, completed or expected by the starting date
- A strong research and publication record in machine learning, deep learning, computer vision, or a closely related area
- The ability to conduct independent research and contribute to the scientific guidance of junior researchers
All applicants should have:
- A solid foundation in machine learning, deep learning, and computer vision
- Strong skills in applied mathematics, probability, and programming, such as Python or C/C++
- Experience with at least one major deep-learning framework, preferably PyTorch
- The ability to work both independently and collaboratively
- Excellent communication skills and fluency in English
Experience relevant to at least one of the projects, including world models, video generation, generative modeling, self-supervised learning, meta-learning, reinforcement learning, multi-agent systems, or embodied AI, is an advantage. Applicants are not expected to have expertise in all these areas.
Level: Excellent
Research Field: Computer science » Modelling tools
Years of Research Experience: 1 - 4
Work Location(s)
Number of offers available: 4
Company/Institute: University of Bern, Institute of Computer Science, Computer Vision Group, Prof. Dr. Paolo Favaro
Country: Switzerland
City: Bern
Postal Code: 3012
Street: Neubrückstrasse 10
Contact
City: Bern
Website: https://www.cvg.unibe.ch/home/
Street: Neubrückstrasse 10
Postal Code: 3012
E-Mail: paolo.favaro@unibe.ch
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