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Employment type:
Internship
Experience required:
Intern
Salary
Salary not provided
About the company:
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!
About the role…
We are looking for a Computational Biology summer intern currently enrolled in an M.S. or Ph.D. program with strong experience in quantitative genetics or population genetics to join our team focused on using these methods to help improve the target identification in the soybean genomes. The pipelines and the results from this intern’s work will contribute to the efforts of building predictive design capabilities.
As an intern you will …
- Work with population level sequencing data to detect association between genotype and phenotype data
- Work with population level genotype data to detect and characterize genome-wide selection signal due to evolutionary and breeding history
- Gain familiarity with performing genomics and bioinformatic analyses on cloud platforms (i.e. AWS)
- Work with computational biologists and bioinformatics scientists to implement the pipeline
- Perform current literature searches to inform the state of the art method
- Present your results to stakeholders within the company
- Become familiar with the norms of working in a private sector biotechnology company
You bring ...
- Competency in R and/or Python for performing genome-wide association using variants such as SNP and deletions as well as familiarity with alignment free methods such as k-mers GWAS
- Familiarity with using population genetics approach to detect selection signal
- Familiarity with analyzing sequencing data using Linux, docker, Jupyter notebook, or R Markdown
- Basic knowledge of the plant genome structure
- Strong communication skills, both written and oral
- A collaborative mindset; open to giving and receiving ideas, perspectives, and feedback
- A strong sense of purpose, and drive to develop unique, high impact solutions
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