NRT-HDR: Intersecting computational and data science to address grand challenges in plant biology

植物对地球上的生命是不可或缺的，它提供食物、能量和氧气，也是许多人造产品的基础。更好地了解植物科学将带来更安全的植物资源，这在全球人口迅速增长的情况下更加重要。基因组学研究极大地促进了我们对植物功能的理解，基因组学的应用产生了数据集，这些数据集可能会给植物科学带来革命性的变化，并导致安全、可靠和可持续的食品和生物燃料生产。为了实现这些结果，迫切需要对植物生物学和计算技能都有了解的科学家。这项授予密歇根州立大学的国家科学基金会研究培训(NRT)奖将通过培训博士生来满足这一需求，这些博士生可以使用先进的计算和数据科学方法来应对植物生物学中的重大挑战。该项目预计将培训大约七十(70)名博士生，其中包括三十八(38)名植物生物学和计算数据科学项目资助的学员。学员将从事研究和课程作业，强调通过利用计算方法来解决植物生物学中的“重大挑战”问题。培训将超越植物生物学的传统基因组学和生物信息学方法，包括处理从分子到生态系统级别的日益异质的多尺度数据所需的计算和建模方面的高级培训。这种类型的培训将允许学生解决复杂的问题，如调查整个植物生命树的基因-表型关系，或为高维植物数据进行机器学习。此外，培训的特点是专业发展机会、外展活动和行业/政府实习，这有助于拓宽学员的职业选择，同时也提高他们与广泛受众沟通的能力。完成培训计划后，学员将对植物和计算科学有一个核心的了解，在跨学科的生物和计算研究方面出类拔萃，并拥有有效的沟通、领导、管理、教学和指导技能。受训人员将由植物科学和计算/数据科学方面的专家共同提供建议。为了实现培训目标，受训人员将参加一项计划，该计划包括：(1)课程和研究活动，以培养一批具有计算科学和植物生物学双重专业知识的受训人员；(2)鼓励科学互动的双周论坛；(3)由受训人员领导的年度研讨会，吸引更多的科学受众，并培养组织和领导技能；(4)行业和政府机构的实习机会；(5)为个人职业目标量身定做的专业发展活动，包括企业家精神；以及(6)通过外联活动，进一步增强受训人员与广泛受众沟通的能力。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。

Plants are indispensable for life on earth, providing food, energy, and oxygen, as well as the basis for many man-made products. A better understanding of plant science will lead to more secure plant resources, which is even more important given the rapidly increasing global population. Genomics research has significantly advanced our understanding about how plants function, with the application of genomics yielding datasets that could revolutionize plant science and lead to safe, reliable, and sustainable production of food and biofuels. To achieve these outcomes, there is a critical need for scientists with both an understanding of plant biology and computational skills. This National Science Foundation Research Traineeship (NRT) award to Michigan State University will address this demand by training doctoral students who can employ advanced computational and data science approaches to address grand challenges in plant biology. The project anticipates training approximately seventy (70) PhD students, including thirty-eight (38) funded trainees from plant biology and computational data science programs. Trainees will engage in research and coursework that emphasize tackling "grand challenge" questions in plant biology by leveraging computational approaches. Training will go beyond the traditional genomics and bioinformatics approaches in plant biology to include the advanced training in computation and modeling required to handle increasingly heterogeneous, multi-scale data from the molecular to ecosystem levels. This type of training will allow students to tackle complex questions such as investigating genotype-phenotype relationships across the Plant Tree of Life or machine learning for high-dimensional plant data. In addition, the traineeship features professional development opportunities, outreach activities, and industry/governmental internships that serve to broaden trainees' career options while also improving their ability to communicate with a wide range of audiences. Upon completion of the training program, trainees will have a core understanding of plant and computational sciences, excel in interdisciplinary biological and computational research, and possess effective communication, leadership, management, teaching, and mentoring skills. Trainees will be co-advised by experts in plant science and computational/data science. To accomplish the training goals, trainees will participate in a program consisting of: (1) curricular and research activities that will create a cohort of trainees with dual expertise in computational sciences and plant biology, (2) a biweekly forum to encourage scientific interactions, (3) a trainee-led annual symposium that engages a wider scientific audience and builds organizational and leadership skills, (4) internship opportunities in industry and government agencies, (5) professional development activities tailored to individual career goals, including entrepreneurship, and (6) public engagement through outreach activities, further bolstering the ability of trainees to communicate with a wide range of audiences. 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 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.