Pairwise is a mission-driven food+tech company dedicated to building a healthier world through better fruits and vegetables. Founded in 2017 by eminent scientists in the gene editing and biotechnology fields, Pairwise holds licenses from Harvard and Massachusetts General Hospital to base editing and high-fidelity enzymes. We also are tuned in to consumer food trends, and we believe that consumers deserve more variety and innovation in their fresh food choices. Our team is primed to deliver that innovation through one of the best gene-editing platforms in food and agriculture. Pairwise has an exclusive 5-year research collaboration with Bayer to develop products in corn, soybean, wheat, canola, and cotton. Plus, Pairwise is developing new types of leafy greens, berries, and stonefruit, with the first product expected in early 2022. Pairwise is based in the start-up friendly Research Triangle Park area of North Carolina.

Pairwise is looking to hire a computational biologist who is interested in leveraging data driven methods for gene discovery and allele design. This role will play a key part in helping to distill meaning and insight from large genomic, structural, genetic and phenotypic data sets. We are looking for a scientist with a PhD or equivalent level of training and the ability to work independently and as part of the team. Your contribution will be critical to helping Pairwise meet a set of aggressive targets and building a culture where science can be fun.



  • PhD or equivalent experience in Computer Science, Statistics, Computational Biology or related fields
  • Demonstrate experience applying machine learning problems in genomics or protein structural genomics
  • Strong understanding transcription factors, protein domains and interactions
  • Strong track record of scientific innovation, formulating research, and developing and executing novel systems and tools
  • Demonstrated ability to deliver scientific results in a cross functional environment
  • Remain current in genomics and machine learning in biology



  • Build computational models to enable dominant allele design for various plant gene targets
  • Build models for principled ranking of genes associated with various trait
  • Design and collaborate with crop scientists, molecular and protein science teams to collect training data sets
  • Collaborate across multifunctional teams to find new insights and drive the innovation culture
  • Collaborate with universities and other scientific organizations to bring diverse thought into Pairwise
  • Strong communication skills to present work to diverse audiences