PostDoc Position at EPFL Frontier Artificial Intelligence Research

EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries.

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.

• 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.

• 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.

• 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.