NRT-HDR: FUTURE Foundations, Translation, and Responsibility for Data Science Impact

计算速度、数据可用性和新型数据分析方法的快速发展催生了一个新的领域：数据科学。这个新领域需要经过严格训练的、跨学科的、有道德责任感的数据科学家。培养“数据科学本地人”的研究人员需要开发一个包容性的跨学科生态系统，由课程和专业发展活动支持，以促进教育和培训。这项授予纽约大学数据科学中心的国家科学基金会研究实习（NRT）奖将建立这样一个名为FUTURE的环境。该项目预计将培养50（50）名博士生，包括20（20）名受资助的受训者，他们来自数据科学和其他学科，如数学、计算机科学、物理学、神经科学、健康科学和心理学。另有145名硕士或博士学生将参与该项目提供的精选课程和专业发展机会。实习将通过严格培训数据科学家来填补一个重要的空白，这些数据科学家：(1)开发方法并利用统计工具来寻找超越传统学科界限的问题的答案；(2)有效沟通，从海量、异构、不确定的数据中提取出清晰的问题；(3)将基础研究见解转化为科学、医学、工业和政府的数据科学实践；并且(4)意识到他们工作的伦理含义。这些目标将通过结合创新的核心课程、通过轮调和实习提供技能转移培训的新的数据助理机制以及交流和创业模块来实现。此外，学员将解决数据科学、机器学习、领域应用和伦理数据使用方面的数学和统计方面的基础研究问题。该项目将创建一个可持续的社会影响模式，并将制作教材和方法，将翻译和责任纳入数据科学课程。FUTURE将以数据科学中心吸引和留住多样化研究生的记录为基础，通过支持多种方法、应用领域和影响途径，创建一个跨学科的研究生培训项目，包括通过设计实现思想的多样性。美国国家科学基金会研究实习生（NRT）计划旨在鼓励开发和实施大胆的、具有潜在变革性的STEM研究生教育培训新模式。该项目致力于通过创新、循证、适应不断变化的劳动力和研究需求的综合培训模式，在高优先级跨学科或融合研究领域对STEM研究生进行有效培训。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Rapid advances in computational speed, data availability, and the development of novel data analysis methods have birthed a new field: data science. This new field requires rigorously trained, cross-disciplinary, and ethically responsible data scientists. Producing researchers who are "data science natives" requires the development of an inclusive, interdisciplinary ecosystem supported by coursework and professional development activities to foster education and training. This National Science Foundation Research Traineeship (NRT) award to the Center for Data Science at New York University will build such an environment entitled FUTURE. This project anticipates training fifty (50) PhD students, including twenty (20) funded trainees, from data science and other disciplines such as mathematics, computer science, physics, neuroscience, health sciences, and psychology. An additional 145 MS or PhD students will engage in select courses and professional development opportunities offered through the project.The traineeship will fill a significant gap by rigorously training data scientists who (1) develop methodology and harness statistical tools to find answers to questions that transcend the boundaries of traditional academic disciplines; (2) effectively communicate to extract crisp questions from big, heterogeneous, uncertain data; (3) translate fundamental research insights into data science practice in the sciences, medicine, industry, and government; and (4) are aware of the ethical implications of their work. These objectives will be achieved by a combination of an innovative core curriculum, a novel data assistantship mechanism that provides training of skills transfer through rotations and internships, and communication and entrepreneurship modules. In addition, trainees will address fundamental research questions in mathematical and statistical aspects of data science, machine learning, domain applications, and ethical data use. The program will create a sustainable model of societal impact and will produce teaching materials and methodologies for incorporating translation and responsibility into data science curricula. FUTURE will build on the Center for Data Science track record of attracting and retaining a diverse cohort of graduate students and will create an interdisciplinary graduate traineeship that includes diversity of thought by design, by supporting a multitude of methodologies, application domains, and avenues for impact.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.