Collaborative Research: Expanding the Reach of Industrial Career Training for Graduate Students

合作研究：扩大研究生工业职业培训的范围

• 批准号: 2016095
• 负责人: David Edwards
• 金额: $ 2.66万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016095&HistoricalAwards=false
• 关键词: Collaborative; Research; Expanding; Reach; Industrial

The 16th annual Graduate Student Mathematical Modeling Camp (GSMMC) will be held June 9–12, 2021 at the University of Delaware, followed the week after by the 36th annual Mathematical Problems in Industry (MPI) workshop, June 14–18, 2021 at the University of Vermont. GSMMC is a mentored, problem-solving workshop, at which small teams of Ph.D. students from across the U.S. are guided through successful mathematical modeling of real-world problems presented by faculty or experienced postdoctoral mentors. Under careful mentoring, student participants build their modeling, teamwork and presentation skills during the week: via the teamwork on modeling and simulating the problems; through the final team presentations made at the end of the week; and in writing the final reports that are produced. Training activities also include numerical simulations and the preparation of a final report outlining their discoveries. These skills are put to use and consolidated the following week at MPI, where industrial participants present immediate modeling challenges facing their industries, on which academic participants (faculty, postdocs, and the Ph.D. students from GSMMC) work. Significant progress on the industrial problems is usually made, and Ph.D. student participants take the lead in presenting the findings to the industrial participants from industry in final presentations at the week's end. In addition to building their skillsets and resumes, student participants are exposed to valuable networking interactions with a range of industrial participants.The GSMMC-MPI program is designed to integrate interdisciplinary research and education for graduate students. The GSMMC is focused on graduate student education and training: its chief intellectual merit lies in the development and analysis, by students, of the mathematical models for the problems presented. Problems are highly interdisciplinary, presenting students with a novel intellectual challenge. With the preparatory training provided by the GSMMC, students are ready for the more open-ended, research-level environment of MPI. The questions posed at MPI challenge participants to design new ways of modeling and analyzing industrial mathematics problems in emerging areas of technology. Mathematical modeling, analytical techniques, numerical simulations, and data analysis must all be used effectively. The collaborative approach to problem solving, which brings together mathematicians ranging from graduate students to experienced faculty, is central to the structure of MPI and provides significant additional training to graduate students, while promoting effective scientific communication. Full details for the Camp may be found at https://www.mathsci.udel.edu/events/conferences/gsmmc-2021, and for MPI at https://mpi2021.w3.uvm.edu/.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.

第 16 届年度研究生数学建模营 (GSMMC) 将于 2021 年 6 月 9 日至 12 日在特拉华大学举行，一周后，第 36 届年度工业数学问题 (MPI) 研讨会将于 2021 年 6 月 14 日至 18 日在佛蒙特大学举行。 GSMMC 是一个受指导、解决问题的研讨会，由博士组成的小团队参加。来自美国各地的学生在教师或经验丰富的博士后导师的指导下，对现实世界的问题进行成功的数学建模。在精心指导下，学生参与者在一周内培养他们的建模、团队合作和演示技能：通过团队合作对问题进行建模和模拟；通过周末进行的最终团队演示；并撰写最终报告。培训活动还包括数值模拟和准备概述他们的发现的最终报告。 这些技能将在接下来的一周在 MPI 得到运用和巩固，行业参与者提出了其行业面临的直接建模挑战，而学术参与者（来自 GSMMC 的教师、博士后和博士生）则致力于解决这些挑战。通常在工业问题上取得重大进展，并且获得博士学位。学生参与者在周末的最终报告中带头向行业参与者展示研究结果。除了培养技能和简历之外，学生参与者还可以与一系列行业参与者进行有价值的网络互动。GSMMC-MPI 项目旨在整合研究生的跨学科研究和教育。 GSMMC 专注于研究生教育和培训：其主要智力优势在于学生对所提出问题的数学模型的开发和分析。问题具有高度跨学科性，给学生带来了新颖的智力挑战。通过 GSMMC 提供的预备培训，学生可以为 MPI 更加开放的研究级环境做好准备。 MPI 提出的问题要求参与者设计新的方法来建模和分析新兴技术领域的工业数学问题。数学建模、分析技术、数值模拟和数据分析都必须得到有效利用。协作解决问题的方法汇集了从研究生到经验丰富的教师的数学家，是 MPI 结构的核心，为研究生提供了大量的额外培训，同时促进有效的科学交流。有关夏令营的完整详细信息，请访问 https://www.mathsci.udel.edu/events/conferences/gsmmc-2021，有关 MPI 的详细信息，请访问 https://mpi2021.w3.uvm.edu/。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进行评估，被认为值得支持。 标准。