NRT-HDR: Harnessing AI for Understanding & Designing Materials (aiM)

在过去的十年中，材料科学研究已经从缓慢的个人实验和计算转向加速数据驱动的人工智能（AI）方法的开始。然而，为了实现快速发现、设计和应用新材料的承诺，培养在人工智能和材料之间接受过培训的新一代劳动力至关重要。这项授予杜克大学的国家科学基金会研究培训，用于理解和设计材料的人工智能（aiM），将为材料和计算机科学家提供综合培训，以推进这一新的融合领域的研究和培训前沿。学生将通过新的课程桥接学科，与融合研究，专业技能和外部实习联系起来，发展人工智能和材料科学方面的专业知识。该NRT将填补先进制造业劳动力的关键空白，促进未来按需材料的开发，用于柔性电子，生物医学植入物，基础设施开发和许多其他领域的重要社会应用。共有50名博士生将在aiM计划中接受培训，其中25人将获得NRT资助，来自计算机科学，数据科学，统计科学以及所有材料学科的学位课程，包括材料科学，物理，化学，和所有工程领域，目标是通过招募多样化的本科生群体，扩大妇女和代表性不足的少数民族的参与，并通过以下方式促进保留文化上一致的指导和包容性的氛围。该aiM计划将提供旨在装备具有竞争力的21世纪世纪专业和技术工作场所技能的学员的核心要素。这些核心要素包括：（1）新开发的跨学科课程，将数据和材料科学与基于问题和项目的学习相融合;（2）通过与国家实验室或行业合作伙伴实习的实际应用进行体验式学习;（3）通过靴子训练营，研讨会，指导，外展机会和行业网络活动进行专业发展。来自材料和计算机科学领域的学生将获得关键的深入交叉培训，整合跨学科的知识和方法，并为发现和创新开发新的框架。新的研究前沿将包括不同材料类别的计算方法，用于模拟和实验数据的材料数据仓库，以及用于科学发现的人工智能方法的开发和改进。该NRT将通过开发基于“材料人工智能”课程的基础知识和应用的并行开放式在线课程模块，以及每年一度的aiM挑战赛，对杜克以外的学生产生深远的影响。在该挑战赛中，世界各地的团队可以在共同的材料数据问题上展开竞争。NSF研究培训（NRT）计划旨在鼓励开发和实施大胆的，为STEM研究生教育培训提供新的潜在变革模式。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相一致的综合培训模式，在高优先级的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NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Over the last decade, there has been a shift in materials science research from slow individual experiments and computation to the beginnings of accelerated data-driven artificial intelligence (AI) approaches. Yet to achieve the promise of rapid discovery, design, and application of new materials, the development of a new generation workforce trained at the nexus of AI and materials is essential. This National Science Foundation Research Traineeship awarded to Duke University, AI for understanding and designing Materials (aiM), will provide integrated training for both materials and computer scientists, to advance the research and training frontiers of this new convergent field. Students will develop expertise in AI and materials science through a new curriculum bridging disciplines, linked with convergent research, professional skills, and external internships. This NRT will fill a critical gap in the advanced manufacturing workforce, facilitating future on-demand materials development for vital societal applications in flexible electronics, biomedical implants, infrastructure development, and many other areas. A total of 50 PhD students will be trained in the aiM program, 25 of whom will be NRT funded, from degree programs in computer science, data science, statistical science, and all materials disciplines including materials science, physics, chemistry, and all engineering fields with the goal of broadening participation of women and underrepresented minorities by recruiting a diverse group of undergraduates and promoting retention through culturally aligned mentoring and an inclusive climate. The aiM program will deliver core elements designed to equip trainees with competitive 21st century professional and technical workplace skills. These core elements include: (1) newly developed transdisciplinary courses fusing data and materials science with problem- and project-based learning; (2) experiential learning through real-world application in internships with national lab or industry partners; and (3) professional development through boot camps, workshops, mentoring, outreach opportunities, and industry networking events. Students from both materials and computer-science domains will gain critical in-depth cross-training that integrates knowledge and methods across disciplines and enables development of new frameworks for discovery and innovation. New research frontiers will incorporate computational methods for different material classes, growing materials data warehouses for simulated and experimental data, and development and improvement of AI methods for scientific discovery. This NRT will impact students far beyond Duke through development of parallel open online course modules based on the fundamentals and applications of “AI for materials” coursework and an annual aiM Challenge in which teams across the world can compete on a common materials data problem.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.