- Analyze and interpret small-molecule and drug discovery datasets using computational biology, bioinformatics, and cheminformatics methods.
- Curate, annotate, and validate chemical and biological datasets to support AI-driven discovery platforms.
- Evaluate compound-target interactions and lead optimization strategies by integrating diverse data sources.
- Provide expert insights on structure-activity relationships and medicinal chemistry approaches.
- Build and implement code-based benchmark tasks reflecting realistic computational drug discovery scenarios.
- Develop reproducible environments and automated testing pipelines to ensure task correctness.
Requirements
- Advanced expertise in Computational Biology, Cheminformatics, or related fields; advanced degree highly valued.
- Solid coding proficiency in Python with experience building tools and pipelines; familiarity with Git, GitHub, and Docker.
- Extensive experience with cheminformatics toolkits such as RDKit, KNIME, or Schr dinger.
- Proven track record in small-molecule drug discovery and virtual screening workflows.
- Comfort working with public chemical and bioactivity databases for scientific analysis.
Application Process
- Easy Apply on LinkedIn
- Check email for next steps
- Participate in resume evaluation & interview stage