About this role
Summary: Join the AIMM Lab at EPFL to develop next-generation generative AI technologies, including diffusion models and foundation models. This methodological role focuses on scalable training algorithms and multimodal learning within a high-performance computing environment.
General
The Artificial Intelligence in Molecular Medicine (AIMM) Lab, led by Prof. Charlotte Bunne at EPFL, sits at the interface of computer science, artificial intelligence, and biomedical applications. The lab is affiliated with both the School of Computer and Communication Sciences and the School of Life Sciences, as well as the EPFL AI Center.
We are recruiting a postdoctoral researcher with strong expertise in modern AI, in particular the development of generative AI technologies such as diffusion models, flow matching, generative transformers, or related architectures. The position is highly methodological and focuses on developing new generative modeling approaches, scalable training algorithms, and foundation model technologies.
The role is suited for candidates with a strong machine learning background who are excited to advance the state of the art in generative AI. Prior experience with biological or biomedical data is not required. The position comes with dedicated access to the Swiss National Supercomputing Centre and the Swiss AI Initiative, and offers opportunities for collaboration across AI, science, and industry.
Research directions include
- Generative AI: development of diffusion models, flow matching, autoregressive models, normalizing flows, or related generative architectures.
- Foundation model development: novel pretraining objectives, scalable architectures, tokenization, and model adaptation strategies.
- Scalable AI training: distributed training, efficient fine-tuning, evaluation, and deployment on large-scale compute.
- Multimodal learning: representation learning and generative modeling across heterogeneous data modalities.
- AI for scientific discovery: methodological advances with potential applications across biomedical and scientific domains.
We are looking for candidates with
- A PhD in machine learning, computer science, applied mathematics, statistics, physics, engineering, or a closely related field, completed or near completion.
- Demonstrated expertise in generative AI, such as diffusion models, flow matching, normalizing flows, VAEs, generative transformers, or related methods.
- Strong programming skills and experience with modern deep learning frameworks.
- Experience with large-scale model training, distributed training, or substantial compute.
- A strong publication record at top-tier machine learning conferences and/or relevant scientific journals.
- Excellent communication skills and enthusiasm for ambitious, interdisciplinary AI research.
We offer
- Competitive EPFL postdoc salary and full social benefits.
- Dedicated compute allocation on CSCS and the Swiss AI Initiative.
- A methodologically ambitious research environment at the interface of generative AI, foundation models, and scientific AI.
- Opportunities for collaboration with academic and industry partners.
- Mentorship toward an independent academic or industry research career.
- An international, collaborative environment at one of Europe's leading technical universities
Activity rate: 100%.
Start date: ideally Fall 2026, with later start dates possible by arrangement.
To apply, please send a CV, a brief statement of research interests (1 page), and the names of two references. More information via https://aimm.epfl.ch. Applications are reviewed on a rolling basis.