Charlotte Bunne

The Artificial Intelligence in Molecular Medicine (AIMM) Lab at EPFL is recruiting a postdoctoral researcher for highly methodological work in frontier artificial intelligence. Led by Prof. Charlotte Bunne, the lab sits at the interface of computer science, artificial intelligence, and biomedical applications, with connections to the School of Computer and Communication Sciences, the School of Life Sciences, and the EPFL AI Center. The project focuses on advancing generative AI and foundation models through new modeling and training methods. The successful candidate will work on diffusion models, flow matching, autoregressive and other generative architectures, as well as scalable training algorithms, model adaptation strategies, multimodal learning, and other foundation-model technologies. The advert emphasizes methodological innovation and development of approaches that can scale to large compute environments and support scientific discovery. The post offers a research environment that combines AI, science, and industry collaboration, with dedicated access to the Swiss National Supercomputing Centre and the Swiss AI Initiative. It is positioned as an ambitious opportunity for a strong machine learning researcher who wants to push the state of the art in generative AI within an international, collaborative setting at one of Europe’s leading technical universities.

The Artificial Intelligence in Molecular Medicine (AIMM) Lab at EPFL is recruiting two postdoctoral researchers to work at the intersection of computer science, artificial intelligence, and the life sciences. Led by Prof. Charlotte Bunne, the lab is affiliated with the School of Computer and Communication Sciences, the School of Life Sciences, and the EPFL AI Center. This opening focuses on the full stack of biological foundation model research. The work spans core architecture design, large-scale pretraining, and integration into agentic interfaces, with a strong emphasis on building models that can support reasoning and decision-support in biological contexts. Research directions include novel pretraining objectives and tokenization methods for biological data, scalable model architectures, multimodal learning across diverse biological data modalities, and translational applications aimed at early drug discovery and biomedical science. The postdocs will collaborate closely with pharmaceutical industry partners and work in a setting with dedicated access to the Swiss National Supercomputing Centre and the Swiss AI Initiative. The position is embedded in an interdisciplinary environment at one of Europe’s leading technical universities, with mentorship aimed at supporting a future independent research career in academia or industry.

The Artificial Intelligence in Molecular Medicine (AIMM) Lab at EPFL is recruiting a postdoctoral researcher for an industry-collaborative project with Novartis on multimodal foundation models. The lab, led by Prof. Charlotte Bunne , works at the interface of computer science and the life sciences and is affiliated with the School of Computer and Communication Sciences, the School of Life Sciences, and the EPFL AI Center. This position centers on building multimodal biological foundation models, with work spanning core architecture design, pretraining at scale, and integration into agentic interfaces. The project brings together methods for multimodal model development and multimodal representation learning, aiming to fuse diverse biological data modalities across scales and to support reasoning and decision-support systems. The research also connects model development to translational applications in early drug discovery using public and Novartis-internal datasets. The postdoctoral researcher will work closely with Novartis Biomedical Research and benefit from dedicated access to the Swiss National Supercomputing Centre (CSCS) and the Swiss AI Initiative. The role is positioned within an international and collaborative environment at one of Europe’s leading technical universities, with mentorship toward an independent academic or industry research career.