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 200 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 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 A Machine Learning Intern you will....
- Be an early contributor to the young, but rapidly growing field of using deep learning and language models on biological sequences
- Train NLP models on protein sequence and biochemical/biophysical data in conjunction with our data scientists and software engineers
- Understand current machine learning literature and consider applications to genomic data
- Gain experience working in a cloud environment with containerized workflows
- Gain exposure to current genomic data
- Develop a basic understanding of modern genetics, protein biochemistry, and genome editing
- Be an active participant in multiple science project teams
- Extensive experience writing code and analyzing data in Python
- Experience with NLP and deep learning methods such as Transformers, CNNs, RNNs, unsupervised learning and reinforcement learning
- Experience with machine learning libraries like TensorFlow and/or PyTorch
- Knowledge of high dimensional data visualization and analysis methods
- A curiosity about protein biochemistry, evolution, and design
- A collaborative mindset; open to giving and receiving ideas, perspectives, and feedback
- Previous experience with protein structural modeling, biochemical analysis, or protein design
- Familiarity with plant metabolic models
- Experience working with any of the following: AWS, Google Cloud, Docker, Git, Agile methodologies
- Employee organized groups, regular social events, and volunteer opportunities provide ways for us to forge personal connections and have fun
- A strong focus on professional development, with both internal and external learning opportunities
- Collaboration opportunities with external stakeholders through interactions with our Scientific Advisory Community
- Comprehensive health, dental, and vision insurance; competitive parental leave
Apply for this job
Inari is proud of our diverse and talented workforce, and committed to maintaining an environment and business practices that reinforce our commitment to equal opportunity. All employment decisions are based solely upon individual competence, track record of performance, and qualifications related to the scope of responsibility of the job, without regard to sex, race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity/reassignment, citizenship, pregnancy or maternity, veteran status, or any other status protected by applicable national, federal, state or local law.