Corteva Agriscience is looking to advance software-based agronomic solutions for growers around the globe using leading edge technologies
Requirements
Hands-on experience with python, data analysis and statistics is required
Relevant experience using machine learning and mechanistic modelling approaches to solve complex problems with mixed variable datasets
Domain knowledge of plant pathology, epidemiology and biological systems
Experience with plant pathology and coding in python is essential for this position
Strong applicants will have completed courses or projects involving data science and/or statistical analysis and modelling
Responsibilities
Model, integrate, and analyze agricultural and weather data
Plant disease and pest management modeling in crops such as corn, soybeans and canola, etc
Develop and execute Python code in high performance distributed Unix/Linux computing environments
Work collaboratively on agile research teams to create innovative software solutions for growers
Design, develop, and support a variety of high-performance software solutions for R&D
Continuously learn and share your technical knowledge with key leaders and project stakeholders
Other
Enrollment in a Masters or Doctoral degree program in mathematics, statistics, plant pathology, data science, computer science or related agricultural engineering field is preferred
3.5+ current cumulative GPA
Excellent problem-solving skills using creative approaches
Ability to work effectively with cross-functional science and engineering teams and business partners
