2 PhD and 2 Postdoctoral Positions in Deep Learning and World Models

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Testo originale dell'annuncio (in inglese)

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 wo