REU Site: Materials Research with Data Science (MAT-DAT)

该奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。最近，由于经济环境和就业方面的考虑，高等教育对更大责任的要求受到了挑战，本科学位的价值受到了挑战。所有学科对具有科学和工程知识以及处理数据能力的专业人员的需求都在增加。这种趋势尤其适用于材料科学和工程领域，在这些领域，既具备领域知识又具备数据科学知识的专业人员非常短缺。因此，培养我们未来的科学家和工程师收集、处理和解释复杂数据的能力至关重要。弥合差距的最有效方法是通过将学习模块和研究经验相结合，采用动手方法对学生进行数据科学培训。在北卡罗莱纳州立大学的REU站点，将招募来自STEM不同学术背景的10名学生，在导师指导下进行为期10周的研究体验。项目将整合机器学习、信息学、统计和数学方法，以及其他基于实验和计算的材料发现的数据科学工具。每年将招募一批不同的参与者，利用与少数族裔服务机构建立的关系，并以研究机会有限的机构为目标。通过这个REU项目，让学生接触数据科学，旨在鼓励他们在stem相关领域从事职业。这个REU网站将努力通过参与北卡罗来纳州社区内的尖端材料工程项目，为年轻的材料工程师提供数据科学方面的培训和实践经验。项目将整合机器学习，材料信息学（MI），统计和数学方法，以及其他基于实验和计算的材料发现的数据科学工具。这个REU网站的重点是提高学生在尖端实验和计算表征技术方面的知识和经验，以及可用于指导新材料发现的MI工具的应用。通过收集数据并将人工智能技术和原理应用于他们的研究项目，学生将阐明工程材料系统的新视角，并将能够直接将这些知识应用于系统设计的改进和/或新材料应用的研究。REU网站活动旨在将学生与他们研究的数据科学和材料信息学方法和方法联系起来，并帮助他们为STEM领域的优秀职业生涯做好准备。有针对性的招募工作将旨在增加代表性不足群体的参与。此外，该计划将通过提供导师培训和经验来加强研究生的教育。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。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).NON-TECHNICAL SUMMARYRecently the value of an undergraduate degree has been challenged as demands for greater accountability in higher education have been driven by economic climate and employment considerations. The demand for professionals with science and engineering knowledge and the ability to handle data is increasing across all disciplines. This trend is especially applicable to materials science and engineering, where professionals with both domain and data science knowledge are in very short supply. Thus, it is vitally important to train our future scientists and engineers to be able to gather, handle and interpret complex data. The most efficient way to bridge the gap is to implement student training in data science using hands-on approach, by combining learning modules and research experience. In this REU Site at North Carolina State University, ten students from various academic backgrounds in STEM will be recruited to spend ten weeks of mentor-guided research experiences. Projects will integrate machine learning, informatics, statistical and mathematical methods, and other data science tools in experimental and computational-based materials discovery. A diverse cohort of participants will be recruited each year, leveraging established relationships with minority-serving institutions, and targeting institutions with limited research opportunities. Exposing the students to data science through this REU program is aimed at encouraging them to pursue careers in STEM-related fields.TECHNICAL SUMMARYThis REU site will strive to provide young materials engineers with training and hands-on experience in data science through their involvement in cutting-edge materials engineering projects within NC State community. Projects will integrate machine learning, materials informatics (MI), statistical and mathematical methods, and other data-science tools in experimental and computational-based materials discovery. This REU site is focused on improvements of student knowledge and experience in cutting-edge experimental and computational characterization techniques and application of MI tools that can be used to guide the discovery of novel materials. Through the collection of data and application of MI techniques and principles to their research projects, the students will elucidate new perspectives of engineered materials systems and will be able to directly apply this knowledge to the improvement of system designs and/or the investigation of novel materials applications. The REU site activities are designed to connect students to the data science and materials informatics methods and approaches of their research and to help prepare them for an excellent career in STEM. Focused recruiting efforts will aim to increase participation by underrepresented groups. In addition, the program will enhance graduate students' education by providing mentorship training and experiences.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.