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The Predictive Agriculture research subfunction of Corteva Agriscience develops and applies design capabilities towards building the next generation of sustainable agricultural systems. Our interdisciplinary team is looking for a creative and curious individual with a willingness to think beyond traditional paradigms in order to shape the future of agriculture. Specifically, we seek to determine how the complexities of genetics, environment, management, and economics generate emergent phenotypes and behaviors that can be holistically managed given modern technologies; the end goals are to help our growers be more productive and sustainable, and to help global agriculture be a force for continued societal improvement.
Candidates should have strong quantitative modeling and applied computational skills, including development, implementation, and execution of activities around dynamical systems, machine learning, numerical analysis, agent-based modeling, optimization, network analysis, and scientific computing, particularly as they apply to disciplines like the life sciences, climatology, or economics.
Successful candidates should be willing to continue to grow and develop their skills in a dynamic and rapidly changing environment as they work with a variety of domain experts to turn theory into practice. The intellectual freedom associated with this position requires that the candidate have demonstrated the ability to actively design and execute interdisciplinary research both independently and collaboratively.
Due to the breadth of expertise required by this position, candidates that some lack requisite skills but whose record demonstrates capacity to think differently, adapt, learn, and persevere through failure are encouraged to apply.
A Ph.D. in any scientific discipline (granted within 4 years of the application deadline). Education with degrees in one of the following fields, or other field with related experience: Complex Systems, Intelligent Systems, Mathematical Biology, Epidemiology, Information Theory, Dynamical Systems, Computer Science
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