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

在过去的几年里，生命科学中的大数据出现了前所未有的爆炸性增长。同样，生物工程的进步有望看到以前看不见的东西，衡量以前无法测量的东西。这种“大数据”和新技术进步的结合，使得在多个尺度上研究植物科学的基本原理成为可能。数字植物科学(DPS)的跨学科研究通过结合计算科学、植物科学和系统工程的方法来利用这些进展来应对农业和生态方面的挑战。因此，下一代研究生必须接受植物科学、生物工程和计算生物学的跨学科培训，以获得实时、多尺度、从微观单细胞到整个生态系统感知、捕获和测量有关植物过程的信息的基本技能。这项授予康奈尔大学的国家科学基金会研究培训(NRT)奖将创造一种融合跨学科团队学习和专业发展的变革性体验，使未来的植物科学家拥有调查、理解和设计植物过程所需的工具，以提高21世纪的植物生产力和可持续性。该项目预计将培训120名研究生，其中包括18名受资助的实习生，他们来自植物生物学、植物育种、植物病理学、土壤和作物科学、生物和环境工程、化学工程和计算机科学等研究生领域。该项目将创建一个互动和创新的核心课程，整合植物科学、计算科学和生物工程，同时在康奈尔社区内外传播这一课程。毕业实习生通过联合授课学习将加强这一核心培训。此外，还将利用新颖的、团队研究轮换经验。由三名研究生组成的团队将在包括计算科学家、生物工程师和植物科学家在内的跨学科教师的指导下，在模拟典型的工业研发环境的基于团队的研究方法的团队环境中协作生成和分析原始“大数据”。研究生培训将扩大到包括沟通和团队合作技能的系统发展，这些技能对于在学术界内外的多种努力中成功的职业生涯至关重要。将利用和扩大康奈尔大学与私营部门之间的伙伴关系，以促进实习生实习和在行业环境中的继续教育经历。最终，该研究生培训计划将开发新的工具和策略，以实时和多尺度地调查植物基因类型、表型和过程。NSF研究培训(NRT)计划旨在鼓励开发和实施大胆的、具有潜在变革意义的STEM研究生教育培训模式。该计划致力于通过创新的、基于证据的、与不断变化的劳动力和研究需求保持一致的综合实习生模式，在高度优先的跨学科或趋同研究领域对STEM研究生进行有效培训。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

There has been an unprecedented explosion of Big Data in the life sciences over the last several years. Likewise, advances in bioengineering promise to see the previously un-seeable and measure the previously immeasurable. This combination of "Big Data" and novel technological advances enables the investigation of fundamental principles in plant science at multiple scales. Interdisciplinary research in Digital Plant Science (DPS) leverages these advances by combining computational science, plant science and systems engineering approaches to respond 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 acquire the foundational skills 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 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. In addition, novel, team research rotation experiences will be utilized. 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. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.