The Position                                                                                                              

 Much of Nurix’s lead finding efforts derive from our DNA Encoded Library group, which regularly screens large (billions of molecules) combinatorial chemical libraries against therapeutic targets of interest. We are seeking a talented and highly motivated cheminformatics/data scientist to lead exploration, analysis, and knowledge finding efforts for these dense, high quality datasets as we seek to increase the information and learnings extracted. Specific responsibilities will include:

  • Develop and improve computational models of SAR gained from DEL selection data, specifically through the implementation of cutting-edge machine learning frameworks
  • Develop summarization and communication techniques to efficiently transfer SAR knowledge identified from DEL selections to target specific project teams
  • Perform analyses on new DEL selection data and collaborate with DEL scientists in hit triage and selection
  • Implement analysis platforms hosting the new analysis methods, to allow for efficient automated and custom analyses
  • Collaborate with DEL scientists to design new data analysis routines and visuals to augment current interpretation of selection data
  • Support DEL scientists in additional cheminformatics tasks, such as filtering building block collections, performing similarity analyses, basic modeling of hits (ie, docking), etc.


  • A Ph.D. in cheminformatics, computational chemistry or related discipline, or BS/MS with demonstrated industry experience
  • Experience in modeling complex chemical data in a drug discovery setting using expertise in cheminformatics, including knowledge of techniques such as QSAR and pharmacophore modeling
  • Mastery of big dataset analysis, and experience with appropriate tools for efficient data processing including
  • Significant coding/development experience in at least one high-level programming language (ie, Python, Java, R), as well as demonstrated knowledge of cheminformatics toolkits (ie, OEChem, RDKit, etc.)
  • Demonstrated experience developing and implementing predictive machine learning models based on chemical structure and biological activity data
  • Demonstrated understanding of basic cheminformatics, such as substructure searching/filtering, molecular property calculations, reaction enumeration, etc.
  • Strong communication skills, along with the ability to work well in multidisciplinary teams, are essential
  • Evidence of creative application of computational approaches to problems of biological or chemical interest is necessary
  • Experience with encoded libraries or combinatorial synthesis is a plus

Fit with Nurix Culture and Values

• Strong team orientation; highly collaborative
• Solutions and results-oriented focus
• Hands-on approach; resourceful and open to diverse points of view

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