PhD Position in Deep Learning
100 %
Institute of Computer Science
Start date: From July 1, 2025 (flexible)
University of Bern – Computer Vision Group
Are you passionate about deep learning, unsupervised learning, and pushing the boundaries of AI? We are offering an exciting opportunity for an outstanding PhD candidate to join the Computer Vision Group (CVG) at the University of Bern, Switzerland.
About the Position
We are looking for a creative and driven PhD student to join a project at the frontier of unsupervised learning, image and video tokenization, and discrete generative models. The research will focus on building powerful representations that bridge visual and textual data, contributing to the development of next-generation AI systems.
• You will conduct original research within a well-established and dynamic research group
• The project is fully funded for 4 years
• Start date: From July 1, 2025 (flexible)
• The position remains open until an excellent candidate is found
• You will conduct original research within a well-established and dynamic research group
• The project is fully funded for 4 years
• Start date: From July 1, 2025 (flexible)
• The position remains open until an excellent candidate is found
Your Profile
We're looking for someone who is curious, ambitious, and eager to work on high-impact research topics in AI.
Must haves:
• A master's degree in Computer Science, Engineering, Mathematics, or a related field
• A solid foundation in machine learning, deep learning, and computer vision
• Strong skills in applied mathematics, probability, and programming (e.g., Python, C/C++)
• Experience with at least one major deep learning framework (e.g., PyTorch, TensorFlow)
• Good communication skills and fluency in English
If you enjoy solving challenging problems and are excited by the prospect of contributing to fundamental advances in deep learning, we want to hear from you!
Must haves:
• A master's degree in Computer Science, Engineering, Mathematics, or a related field
• A solid foundation in machine learning, deep learning, and computer vision
• Strong skills in applied mathematics, probability, and programming (e.g., Python, C/C++)
• Experience with at least one major deep learning framework (e.g., PyTorch, TensorFlow)
• Good communication skills and fluency in English
If you enjoy solving challenging problems and are excited by the prospect of contributing to fundamental advances in deep learning, we want to hear from you!
What We Offer
Join a collaborative and innovative research environment
• Be part of a vibrant academic team and work alongside world-class researchers
• Access to state-of-the-art compute infrastructure
• Opportunities to publish at top-tier conferences and participate in the global research community
• Funding to attend international conferences, workshops, and training programs
• A competitive salary, including additional compensation for teaching assistance
• Live in Bern, a beautiful, livable city in the heart of Switzerland with outstanding quality of life
• Be part of a vibrant academic team and work alongside world-class researchers
• Access to state-of-the-art compute infrastructure
• Opportunities to publish at top-tier conferences and participate in the global research community
• Funding to attend international conferences, workshops, and training programs
• A competitive salary, including additional compensation for teaching assistance
• Live in Bern, a beautiful, livable city in the heart of Switzerland with outstanding quality of life
Contact
Prof. Dr. Paolo Favaro
Computer Vision Group
Tel. +41 (0)31 684 44 51 (office)
Tel. +41 (0)31 684 49 14 (secretary)
favaro@inf.unibe.ch
www.cvg.unibe.ch
Computer Vision Group
Tel. +41 (0)31 684 44 51 (office)
Tel. +41 (0)31 684 49 14 (secretary)
favaro@inf.unibe.ch
www.cvg.unibe.ch
Interested?
Please send your application through the submission portal link http://cvg.unibe.ch/vacancies/
Applications submitted directly via email will not be considered.
Please send your application through the submission portal link http://cvg.unibe.ch/vacancies/
Applications submitted directly via email will not be considered.
