Collaborative Research: A Two-Week Mentored Program to Prepare Graduate Students for Industrial Careers

合作研究：为期两周的指导项目，帮助研究生为工业职业做好准备

• 批准号: 1916281
• 负责人: David Edwards
• 金额: $ 1.86万
• 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: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1916281&HistoricalAwards=false
• 关键词: Collaborative; Research; Two; Week; Mentored

The 15th annual Graduate Student Mathematical Modeling Camp (GSMMC) will be held June 12-15, 2019 at the University of Delaware, followed the week after by the 35th annual Mathematical Problems in Industry (MPI) workshop, June 17-21, 2019 at the New Jersey Institute of Technology. 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 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 involves 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 both events may be found athttps://www.mathsci.udel.edu/events/conferences/gsmmc-2019https://web.njit.edu/~rmoore/MPI2019/MPI2019home.phpThis 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15届年度研究生数学建模营（GSMMC）将于2019年6月12日至15日在特拉华州大学举行，随后的一周是第35届年度工业数学问题（MPI）研讨会，2019年6月17日至21日在新泽西理工学院举行。GSMMC是一个指导，解决问题的研讨会，在小团队的博士。来自美国各地的学生通过由教师或经验丰富的博士后导师提出的真实世界问题的成功数学建模进行指导。在认真的指导下，学生参与者在一周内建立了他们的建模，团队合作和演示技巧：通过建模和模拟问题的团队合作;通过在周末进行的最终团队演示;并编写最终报告。培训活动还包括数值模拟和编写概述其发现的最后报告。 这些技能将在接下来的一周在MPI上得到使用和巩固，在那里，工业参与者提出了他们所在行业面临的直接建模挑战，学术参与者（教师，博士后和博士）将在此基础上进行建模。GSMMC的学生）工作。在工业问题上通常会取得重大进展，学生参与者在周末的最后报告中率先向来自行业的参与者介绍研究结果。除了建立自己的技能和简历，学生参与者接触到有价值的网络互动与一系列的行业参与者。GSMMC-MPI计划旨在整合跨学科的研究和教育的研究生。GSMMC专注于研究生教育和培训：其主要智力价值在于学生对所提出问题的数学模型的开发和分析。问题是高度跨学科的，给学生带来了新的智力挑战。通过GSMMC提供的预备培训，学生已经为MPI的更开放的研究级环境做好了准备。MPI提出的问题挑战参与者设计建模和分析新兴技术领域工业数学问题的新方法。数学建模、分析技术、数值模拟和数据分析都必须有效地使用。协作解决问题的方法，涉及从研究生到经验丰富的教师的数学家，是MPI结构的核心，并为研究生提供了重要的额外培训，同时促进了有效的科学交流。这两个事件的全部细节可以在以下网站上找到：httpps：www.mathsci.udel.edu/events/conferences/gsmmc-2019https://web.njit.edu/~rmoore/MPI2019/MPI2019home.phpThis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。