Cryo-EM reveals mechanisms of natural RNA multivalency
π-PrimeNovo: accurate non-autoregressive deep learning for de novo peptide sequencing
ViraHinter: a dual-modal artificial intelligence framework for predicting virus-host interactions
Accurate de novo sequencing of the modified proteome with OmniNovo
MassNet: billion-scale AI-friendly mass spectral corpus enables robust de novo peptide sequencing
We focus on AI for science.
Agentic systems for scientific discovery
Autonomous reasoning and workflow automation for evidence synthesis, target discovery, and experimental design.
Foundation models for drug discovery
Developing foundation models that connect sequence, structure, and function across genomes, proteins and small moleculars.
Virtual cell modeling and simulation
Building computational models that simulate cellular processes, integrating multi-omics data for biological discovery.
We are recruiting.
BEAM Lab is actively recruiting at Shanghai AI Lab and Fudan University. We focus on AI for Science and Large Language Models.
Candidates with backgrounds in CS, Math, Physics, Biology, or Chemistry are highly valued. Send your CV and transcripts to:
[email protected]PhD Students
Open for Fall 2027
Research Interns
Open positions available
Research Scientists
Open positions available
Postdocs & RAs
Open positions available
BEAM LAB
BEAM (Biological Engineering And Machine learning in Bioinformatics) Lab develops AI methods for scientific discovery, with emphasis on foundation models connecting biomolecular sequence, structure, and function.
Biomolecular modeling: proteins, antibodies, and RNA
Structure prediction/design, proteomics, and AI-driven drug discovery
Virtual cell modeling and simulation
Agentic science for autonomous reasoning and research workflows
We are hiring!
BEAM Lab is actively recruiting self-motivated PhD students (Closed for Fall 202...
FoldBench published in Nature Communications
Our paper Benchmarking all-atom biomolecular structure prediction with FoldBench...