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National Science Foundation Research Traineeship (NRT)

NRT: Team training to develop new hardware and software applications for digital plant science across multiple scales

The last several years have witnessed an unprecedented explosion of Big Data in the plant sciences, whereas advances in bioengineering promise to see the previously un-seeable, and measure the previously immeasurable. Interdisciplinary research in Digital Plant Science (DPS) couples computational science with plant science and systems engineering to understand plant structure and function in response to agricultural and ecological challenges. 

Accordingly, this next generation of graduate students must receive cross-disciplinary training in plant science, bioengineering, and computational biology to provide the foundational skills required to sense, capture, and measure information about plant processes in real time and at multiple scales, from microscopic single cells to entire ecosystems.

This National Science Foundation Research Traineeship (NRT) award to Cornell University will create a transformative experience that integrates interdisciplinary team learning and professional development to equip future plant scientists with the tools needed to investigate, comprehend, and engineer plant processes to improve plant productivity and sustainability in the 21st century. The project anticipates training approximately 120 graduate students, including 18 funded trainees from the graduate fields of Plant Biology, Plant Breeding, Plant Pathology, Soil and Crop Sciences, Biological and Environmental Engineering, Chemical Engineering, and Computer Science. 

This project will create an interactive and innovative core curriculum that integrates plant science, computational science, and bioengineering, while disseminating this curriculum throughout and beyond the Cornell community. Graduate trainee learning through co-instruction will reinforce this core training. Novel, Team Research Rotation experiences will be instigated, wherein teams of three graduate students, mentored by cross-disciplinary faculty comprising computational scientists, bioengineers, and plant scientists, will collaborate to generate and analyze original “Big Data” in a group environment that simulates the team-based research approaches that typify industrial research and development settings.

Graduate student training will be broadened to include the systematic development of communication and team-working skills that are essential for successful careers in multiple endeavors, both within and outside of academia. Partnerships between Cornell and the private sector will be exploited and extended, to facilitate trainee internships and continuing-education experiences in an industry setting.  Ultimately, this graduate training program will develop new tools and strategies to investigate plant genotypes, phenotypes, and processes in real time and at multiple scales.

For more information, contact Mike Scanlon (mjs298@cornell.edu)