University of Bern
3 days ago
PhD and Postdoctoral Positions in Deep Learning, Self-Supervised Learning, Generative AI, and Meta-Learning at the University of Bern University of Bern in Switzerland
Degree Level
PhD, Postdoc
Field of study
Computer Science
Funding
All positions are fully funded within their respective projects. The project is fully funded for four years, and the University of Bern offers a competitive salary according to its regulations, with additional compensation for teaching duties. Funding for international conferences, workshops, and training programs is included.
Country
Switzerland
University
University of Bern

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About this position
University of Bern, Computer Vision Group (CVG) is advertising 2 PhD and 2 postdoctoral positions in deep learning and computer vision.
The openings span two research projects: Collaborative World Models and Self-Supervised and Meta-Learning for Rapid Adaptation. Research topics include deep learning, self-supervised learning, generative AI, generative video modeling, memory-augmented world models, test-time adaptation, decision-making, meta-learning, novel datasets, benchmark environments, and learning algorithms and architectures. The first project also connects to embodied AI and robotics.
These positions are based at the University of Bern in Switzerland and are carried out in a dynamic research group with access to state-of-the-art computing infrastructure, including the Swiss AI large-scale GPU cluster. The second project is conducted in close collaboration with Prof. Andrea Vedaldi at the University of Oxford.
Funding: all positions are fully funded within their respective projects. The project duration is stated as four years, and the university provides a competitive salary plus additional compensation for teaching duties. Support is also available for conferences, workshops, and training.
Eligibility highlights: PhD applicants should have a master’s degree in computer science, engineering, mathematics, or a related field by the start date. Postdoctoral applicants should have a PhD in a related field and a strong publication record. For all applicants, strong foundations in machine learning, deep learning, computer vision, applied mathematics, probability, and programming are expected; PyTorch experience is preferred; English fluency is required.
Application: submit your application via the portal, choose a project, and then select the PhD or postdoctoral track. Applications sent directly by email will not be considered. The post says applications are reviewed until excellent candidates are found. Start date is October 1, 2026, or by agreement.
Funding details
All positions are fully funded within their respective projects. The project is fully funded for four years, and the University of Bern offers a competitive salary according to its regulations, with additional compensation for teaching duties. Funding for international conferences, workshops, and training programs is included.
What's required
PhD applicants need a master’s degree in computer science, engineering, mathematics, or a related field completed or expected by the start date, plus a strong interest in fundamental research in machine learning and artificial intelligence. Postdoctoral applicants need a PhD in computer science, engineering, mathematics, or a related field completed or expected by the start date, plus a strong research and publication record in machine learning, deep learning, computer vision, or a closely related area. 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; ability to work independently and collaboratively; excellent communication skills; and fluency in English. Experience in world models, video generation, generative modeling, self-supervised learning, meta-learning, reinforcement learning, multi-agent systems, or embodied AI is an advantage.
How to apply
Apply through the application portal by choosing a project and then selecting either the PhD or postdoctoral application. Applicants may apply to both projects where appropriate. Do not apply by email, as email submissions will not be considered.
More information can be found here
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