Who are we, and what do we do? 

Corteva Agriscience is the only major agriscience company in the world completely dedicated to agriculture. Our purpose is to enrich the lives of those who produce and those who consume, ensuring progress for generation to come. Our inspiration is to be a market shaper, driving the next generation of agriculture products that help farms and farmers flourish and through partnering with society becoming the most trusted partner in the global agriculture and food community. With a global footprint and over 20,000 employees, Corteva is building the future of agriculture and leading breakthroughs in the innovation and application of science and technology that will better the lives of people all over the world and fuel the progress of humankind.

Join a fast-paced research & development team that is using leading edge technologies to advance software-based agronomic solutions for growers around the globe. As an Agronomic Data Science & Pathology Intern at Corteva, you will have a unique opportunity to learn, grow, and expand your knowledge as you help research and develop the digital crop advisor of tomorrow.  Experience with plant pathology and coding in python is essential for this position.  Applicants should also have a drive for excellence, excel in using creative approaches to solving complex problems, and possess an innovative mindset.  Strong applicants will have completed courses or projects involving data science and/or statistical analysis and modelling. Affinity with agriculture, pathology, epidemiology and biological systems is an advantage.

What You'll Do:

Model, integrate, and analyze agricultural and weather dataPlant disease and pest management modeling in crops such as corn, soybeans and canola, etcDevelop and execute Python code in high performance distributed Unix/Linux computing environmentsWork collaboratively on agile research teams to create innovative software solutions for growersDesign, develop, and support a variety of high-performance software solutions for R&DContinuously learn and share your technical knowledge with key leaders and project stakeholders

What You'll Bring:

Enrollment in a Masters or Doctoral degree program in mathematics, statistics, plant pathology, data science, computer science or related agricultural engineering field is preferred3.5+ current cumulative GPAExcellent problem-solving skills using creative approachesHands-on experience with python, data analysis and statistics is requiredRelevant experience using machine learning and mechanistic modelling approaches to solve complex problems with mixed variable datasetsDomain knowledge of plant pathology, epidemiology and biological systemsAbility to work effectively with cross-functional science and engineering teams and business partners