About Inari...

Inari is the SEEDesign™ company. We embrace the diversity and complexity of nature in every aspect of our business to drive innovation – to push the boundaries of what is possible. Through our unrivaled technology platform, Inari uses predictive design and advanced multiplex gene editing to develop step-change products. We are taking a nature positive approach to unlock the full potential of seed that will transform the food system. The results will lead to more productive acres delivering value creation for farmers and a more sustainable future for our planet.

Our success is dependent on great minds, collaborating to generate bright ideas and deliver exceptional outcomes.

We have over 270 employees, with research sites in Cambridge, MA (USA) and Ghent (Belgium), as well as a product development site in West Lafayette, IN (USA). We’ve deliberately built a team that brings diversity of thought to all aspects of our business, to generate new ideas, approaches, and ways of operating. And we've intentionally combined experience with potential, bringing agriculture industry experts with the desire to innovate together with bright minds from academia, human therapeutics, software, and consulting. If you want to be part of a diverse and inclusive team developing unique solutions to feed the world while protecting our planet’s natural resources, we’d love to hear from you!

The Role

We are looking for a summer intern currently enrolled in an M.S. or Ph.D. program with strong experience in computational biology, quantitative or population genetics to join our team focused on identifying editing targets to improve complex traits in crops. The internship will last for three months. 

As an Intern, you will…

  • Work with large scale sequencing and genotyping data to discover novel genotype-to-phenotype associations
  • Gain familiarity with performing computational biology analyses on modern cloud infrastructure (ie AWS) 
  • Work with Inari’s computational biologists to apply tools from other disciplines to improve editing target identification in plant genomes 
  • Use the scientific literature inform new analyses and hypotheses
  • Present your results to stakeholders within the company
  • Become familiar with the norms of working in a private sector biotechnology company 

You bring…

  • Competency with one or more of the following (Python, R, Julia) and a Linux/UNIX computing environment
  • An understanding of linear mixed models with demonstrated applications to marker-trait and gene-trait association (GWAS, PheWAS, TWAS, QTL mapping, variance decomposition, etc) and/or polygenic risk score prediction / genomic prediction
  • Familiarity with analyzing large-scale genetic variant datasets using public tools 
  • Ability to work in a team in a fast-paced, cross-functional environment
  • Ability to manage ambiguity and to exchange constructive feedback
  • Adaptability and enthusiasm for new challenges, innate curiosity, and a passion for learning
  • Curiosity and a desire to continuously learn and have a meaningful impact
  • Creative and strategic thinking, good problem-solving skills, willingness to be bold and take risks, and the ability to recognize and learn from failures

Bonus qualifications

  • Previous experience working with plant genomic data
  • Familiarity with the integration of large datasets (RNAseq, metabolomics, proteomics, etc)
  • Familiarity with plant or animal breeding methodologies
  • Experience working with any of the following: AWS, Google Cloud, Docker, Git, Agile methodologies

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