About This Job

We invite you to help us shape the future of agriculture. At Syngenta, we believe every employee has a role to play in safely feeding the world and taking care of our planet. To support that challenge, the North America Trait Introgression (NA TI) team is currently looking for a skilled individual to join our group of TI Pipeline, Simulation, and Applied Genetic Scientists, and help us accelerate the delivery of high-quality traited elite germplasm to the business, contributing to superior product performance and genetic gain. As an intern in Genotype x Trait (GxT) Genomic Prediction Modeling, you will interact with TI, Trait Delivery, and Breeding to develop predictive models that use both genetically engineered as well as native trait, along with genome-wide genetic signal, to predict the field performance of traited elite corn germplasm.

As an intern at Syngenta, you have the opportunity to work alongside some of the brightest minds in the industry, and work on real projects finding real solutions. Work with us and you’ll get:

• Competitive wages
• Ongoing career development resources
• The opportunity to work on meaningful, innovative projects that solve problems
• A culture that celebrates diversity & inclusion, promotes professional development, and offers flexible work options to meet both your work and personal needs

Estimated Duration: March - August 2023

You will:

• Use historical TI and advanced hybrid performance data to develop a genomic selection algorithm that accounts for GM trait effect, large-effect QTL associated with GM traits, and their interaction, to predict field performance in elite corn germplasm
• Develop and train predictive models for main female and male trait stacks, and implement their use to select among trait versions, select new elite lines for conversion, and support selection of commercial products
• Develop and validate appropriate training datasets for the prediction of both inbred and hybrid traited corn products
• Elucidate the effects of GxT interactions in elite corn germplasm, and potentially discover genetic signal associated with expected and/or unexpected phenotypic effects

Syngenta Seeds is one of the world’s largest developers and producers of seed for farmers, commercial growers, retailers and small seed companies. Syngenta seeds improve the quality and yields of crops. High-quality seeds ensure better and more productive crops, which is why farmers invest in them. Advanced seeds help mitigate risks such as disease and drought and allow farmers to grow food using less land, less water and fewer inputs. Syngenta Seeds brings farmers more vigorous, stronger, resistant plants, including innovative hybrid varieties and biotech crops that can thrive even in challenging growing conditions. Syngenta Seeds is headquartered in the United States.

What You must have:

• Enrollment in a M.S. or Ph.D. program in data science, molecular biology, genetics/genomics, quantitative genetics, bioinformatics, or similar; OR
• Enrollment in a Bachelor’s degree program in data science, quantitative genetics, bioinformatics, molecular biology, or similar. Current Sophomore or Junior standing and proven experience is preferred
• Knowledge of and experience with programming languages, such as R, Python
• Knowledge of and experience with predictive analytics using Bayesian, Machine Learning, or other algorithms
• Understanding and/or experience with genomic prediction/genomic selection
• Fluent in English
• Ability to communicate clearly with both plant/biology scientists and breeders

What you might also contribute to the team:

• Experience working with biological systems
• Experience with large molecular and phenotypic data sets
• Familiarity with plan biology and/or plant breeding
• Familiarity with QTL, GM trait, and native trait concepts

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Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity, marital or veteran status, disability, or any other legally protected status.

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