Humans, animals, and other living beings have a natural ability to autonomously learn throughout their lives and quickly adapt to their surroundings, but computers lack such abilities. Our goal is to bridge such gaps between the learning of living-beings and computers. We are machine learning researchers with an expertise in areas such as approximate inference, Bayesian statistics, continuous optimization, information geometry, etc. We work on a variety of learning problems, especially those involving supervised, continual, active, federated, online, and reinforcement learning. Please check out research and publications pages for a more exhaustive overview.
If you are interested in joining us, see the people page and the vacancies below for current opportunities.
Vacancies
PostDoc at TU Darmstadt:Two PostDoc Positions at TU Darmstadt from Sep. 1st 2026; closing June 21st, 2026. [details]
PhD at TU Darmstadt:Four PhD Positions at TU Darmstadt from Sep. 1st 2026; closing June 21st, 2026. [details]
Research Scientist at Polymathic AI:Several Research Scientist Positions in collaboration with Polymathic AI from Apr. 1st 2026. [details]
PostDoc at Polymathic AI:Several PostDoc Positions in collaboration with Polymathic AI from Apr. 1st 2026. [details]
Internship (Overseas Student Collaboration) Program:Masters or PhD students from overseas, collaborative research for 3-12 months with financial support. [details]
Junior Research Associate:Part-time positions at RIKEN for young researchers enrolled in Japanese university PhD programs. [details]
International Program Associate:RIKEN’s joint graduate school program for non-Japanese PhD candidates at any graduate school. [details]
For all positions, send inquiries to jobs-abi [at] googlegroups.com.News
Workshop on Continual Adaptation at Scale: Towards Sustainable AI accepted at ICML 2026
Federated ADMM from Bayesian Duality by Thomas Möllenhoff et al. accepted at ICLR 2026