IGE: Integrating Data Science into the Applied Mathematics PhD: Generalized Skills for Non-Academic Careers

这个国家科学基金会研究生教育创新（IGE）奖给亚利桑那大学将通过整合人工智能（AI）和在国家实验室（NL）和工业实验室（IL）实现非传统的研究职业，彻底改变应用数学（AM）的研究生课程。AM是一门多功能的科学，在所有STEM学科的前沿研究中发挥着至关重要的作用。通过将人工智能注入AM，该研究项目团队旨在将正在进行的人工智能革命推向新的高度，解决新兴的国家和全球挑战。亚利桑那大学（AM@UA）的应用数学研究生跨学科项目将与NLS和IL合作，作为这种创新研究生培养模式的试验场。总体目标是建立一个研究人员的管道，配备了解决复杂问题和促进有利于整个社会的解决方案所需的技能。通过使AM课程现代化并使其与国家安全需求保持一致，我们不仅推进了研究领域，而且吸引和留住了包括女性和代表性不足的少数民族在内的多元化学生群体，以追求非学术STEM职业。该项目将为其他AM博士提供蓝图。AM@UA项目的目标是通过综合方法来改变STEM研究生教育，弥合经典AM和新型AI学科之间的差距。该项目旨在了解和解决学术界和非学术STEM领域之间跨学科鸿沟的挑战。随着国家目前对优先领域的关注，我们的目标是探索跨越这些鸿沟的有效战略，以满足对专业技能日益增长的需求。拟议的社会科学研究将评估这些方法的有效性，并深入研究其成功的基本过程。该项目将引入创新的三方合作，涉及一名博士生，他们的大学顾问和一名来自国家或工业实验室的联合顾问。这种合作模式将提供长期的研究机会和实习机会，培养学生在传统和现代AM（包括数据科学和人工智能）方面的专业知识。该项目的核心是在STEM研究生教育中产生新的知识，通过将人工智能融入AM来推动该领域的发展，以创建一支能够应对人工智能驱动和人工智能驱动的挑战的劳动力队伍。通过强调多样性和包容性，该项目旨在吸引和留住一批有才华的学生，确保他们为各种非学术STEM职业做好充分准备。通过与Raytheon和能源部实验室等受人尊敬的合作伙伴合作，项目团队将进一步弥合学术与行业之间的差距，促进研究生在这些环境之间的无缝过渡。该项目的成果将为研究生应用数学劳动力培训的通用模型铺平道路，适用于其他AM博士。计划和国家和工业实验室。最终，这一奋进将通过培养一支具有全球竞争力的多元化劳动力队伍来应对当今最紧迫的挑战，为社会做出重大贡献。研究生教育创新（IGE）计划专注于研究生教育研究。IGE的目标是试验、测试和验证研究生教育的创新方法，并产生将这些方法推广到更广泛的社区所需的知识。该奖项反映了NSF的法定使命，并被认为值得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来支持。

This National Science Foundation Innovations in Graduate Education (IGE) award to the University of Arizona will revolutionize the graduate program in Applied Mathematics (AM) by integrating Artificial Intelligence (AI) and enabling non-traditional research careers in National Laboratories (NLs) and Industrial Laboratories (ILs). AM is a versatile science that plays a crucial role in cutting-edge research across all STEM disciplines. By infusing AI into AM, this research project team aims to take the ongoing AI revolution to new heights, solving emerging national and global challenges. The Applied Mathematics Graduate Interdisciplinary Program at the University of Arizona (AM@UA) will serve as a testing ground for this innovative graduate training model, in partnership with NLs and ILs. The overarching goal is to create a pipeline of researchers equipped with the skills needed to address complex issues and foster solutions that benefit society as a whole. By modernizing the AM curriculum and aligning it with national security needs, we not only advance the field of study but also attract and retain a diverse group of students, including women and underrepresented minorities, to pursue non-academic STEM careers. This project will provide a blueprint for other AM Ph.D. programs nationwide, forging a path towards a diverse, competitive, and future-ready workforce capable of thriving in the era of AI.The AM@UA project is driven by the vision of transforming STEM graduate education through an integrated approach that bridges the gap between classic AM and novel AI disciplines. The project seeks to understand and address the challenges of crossing disciplinary divides between academia and non-academic STEM domains. With the current national focus on areas of priority, we aim to explore effective strategies for crossing these divides to meet the growing demand for specialized skills. The proposed social science research will evaluate the effectiveness of these approaches and delve into the underlying processes responsible for their success. The project will introduce innovative triadic collaborations involving a PhD student, their university advisor, and a co-advisor from a national or industrial laboratory. This collaboration model will offer long-term research opportunities and internships, nurturing students' expertise in both traditional and contemporary AM, including data science and AI.At its core, the project will generate new knowledge in STEM graduate education, advancing the field by integrating AI into AM to create a workforce capable of tackling AI-driven and mathematics-enabled challenges. Through its emphasis on diversity and inclusion, the project aims to attract and retain a talented pool of students, ensuring they are well-prepared for a variety of non-academic STEM careers. By collaborating with esteemed partners like Raytheon and Department of Energy laboratories, the project team will further bridge the academic-industry gap, facilitating seamless transitions for graduate students between these settings. The outcomes of this project will pave the way for generalized models of graduate applied mathematics workforce training, applicable to other AM Ph.D. programs and national and industrial laboratories. Ultimately, this endeavor will make significant contributions to society by nurturing a diverse and globally competitive workforce equipped to address the most pressing challenges of today.The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.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.