Research Associate, Functional Genomics

Research Associate, Functional Genomics

Epic Bio | South San Francisco


Who Are We?


Our client's company is based on the science of our founder, one of the original CRISPR co-inventors who then furthered the technology so that DNA does not need to be cut to accomplish gene regulation. They are well funded and still in stealth mode with plans to emerge early next year.


  • Develop the high-throughput screening for a portfolio of cell therapy applications
  • Develop DNA constructs and CRISPR libraries
  • Develops, evaluates, optimizes and implements new technologies, laboratory protocols, and methodologies for biochemical and cell-based assays
  • Provide expert support for multiplexing and scaling biological readouts across our broader scientific team
  • Maintain familiarity with the relevant current literature and its application to multiplexing readouts and cell therapy
  • Coordinate tasks across multiple projects, demonstrating prioritization and planning
  • Interpret and effectively execute experiments in line with project timelines and goals


  • BS in molecular biology, biotechnology, pharmaceutical, stem cell or related fields, with 2+ years of relevant research experience in industry or academia
  • Experience with high-throughput functional CRISPR screening; prior experience using gene editing, RNAi, CRISPRa/i, or CRISPR KO strategies
  • Working knowledge of NGS technologies and workflows
  • Ability to quickly learn new skills and knowledge on the job, demonstrate productivity, and deliver high-quality results

Exceptional candidates will also possess the following skills:

  • Experience in cellular reprogramming, adult stem cell such as HSCs, MSCs or SSCs culture
  • Familiarity with R or similar environments for pipelining of routine data analysis
  • Collaborative experience with computational biologists and/or software engineers to help develop and use novel tools for construct design, experimental planning and/or data analysis
  • Experience with multiplexing/barcoding approaches for scaling experimental throughput