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

过去几年，生命科学领域的大数据出现了前所未有的爆炸式增长。 同样，生物工程的进步有望看到以前无法看到的事物并测量以前无法测量的事物。 “大数据”与新颖技术进步的结合使得能够在多个尺度上研究植物科学的基本原理。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方法来利用这些进步来应对农业和生态挑战。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，以获得从微观单细胞到整个生态系统的多尺度实时感知、捕获和测量植物过程信息的基本技能。康奈尔大学获得的国家科学基金会研究实习 (NRT) 奖将创造一种变革性的体验，将跨学科团队学习和专业发展融为一体，为未来的植物科学家提供调查、理解和设计植物过程所需的工具，从而提高 21 世纪的植物生产力和可持续性。该项目预计培养120名研究生，其中18名受资助的研究生，分别来自植物生物学、植物育种、植物病理学、土壤与作物科学、生物与环境工程、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，同时在康奈尔大学社区内外传播该课程。研究生学员通过共同指导的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，在由计算科学家、生物工程师和植物科学家组成的跨学科教师的指导下，将在团队环境中合作生成和分析原始“大数据”，模拟工业研究和开发环境中典型的基于团队的研究方法。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，这对于学术界内外多项事业的成功职业至关重要。康奈尔大学与私营部门之间的合作伙伴关系将得到利用和扩展，以促进实习生在行业环境中的实习和继续教育经验。最终，这个研究生培训项目将开发新的工具和策略来实时、多尺度地研究植物基因型、表型和过程。 NSF 研究培训 (NRT) 计划旨在鼓励为 STEM 研究生教育培训开发和实施大胆的、具有潜在变革性的新模式。该计划致力于通过创新、循证且符合不断变化的劳动力和研究需求的综合培训模式，对高度优先的跨学科或融合研究领域的 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.