Home
FLAIR Lab · Mila & Université de Montréal
Machine learning for the language of life.
We develop methods across the language modeling pipeline for biological sequences such as proteins, genomes, and transcriptomes, with applications in drug discovery.
Recent news
| Jul 23, 2026 | New preprint: High-resolution dissection of concept acquisition in different families of protein language models. We map where biological concepts emerge in ESM2 and AMPLIFY, from physicochemical properties to structure, and find that data and compute matter more than model size. With Shawn T. Whitfield, Tom Marty, Robert M. Vernon, Christopher James Langmead, and Dhanya Sridhar. In collaboration with Amgen. |
|---|---|
| Jul 08, 2026 | New preprint: A systematic analysis of machine learning pipelines for robust antimicrobial resistance prediction. We identify what design choices matter for genomic antimicrobial-resistance prediction. With Alex Aselstyne, Enamundram Naga Karthik, Meriem El Azami, Romain Pogorelcnik, and Sarath Chandar. In collaboration with bioMérieux. |
| Apr 23, 2026 | Proud of Lola Le Breton, who presented NeoBERT: A Next Generation BERT at ICLR 2026 as part of the TMLR journal track. With John X. Morris, Mariam El Mezouar, and Sarath Chandar. |
| Feb 27, 2026 | New preprint: CoPeP: Benchmarking Continual Pretraining for Protein Language Models. A benchmark for studying how protein language models can keep up with new data without retraining from scratch. With Darshan Patil, Pranshu Malviya, Mathieu Reymond, and Sarath Chandar. In collaboration with Genentech. |
| May 22, 2025 | New preprint: Structure-Aligned Protein Language Model. We bring 3D structural information into protein language models via a lightweight post-training. With Can Chen, David Heurtel-Depeiges, Robert M. Vernon, Christopher James Langmead, and Yoshua Bengio. In collaboration with Amgen. |
Open positions
We are recruiting one PhD student. Get in touch.