REU Site: ACRES: Advanced Computational Research Experience for Students
REU 网站:ACRES:学生的高级计算研究体验
基本信息
- 批准号:2349002
- 负责人:
- 金额:$ 45.49万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2024
- 资助国家:美国
- 起止时间:2024-02-01 至 2027-01-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The application of large-scale computing power to solve problems is becoming more and more common in science and industry. It is thus vital to equip the next generation with the skills necessary to meet this need. This award will fund a summer Research Experience for Undergraduates program called “Advanced Computational Research Experiences for Students” or “ACRES” at Michigan State University (MSU) that will offer students the opportunity to conduct cutting-edge research in computational and data science under the supervision of faculty who are recognized experts in their disciplines. Over 10-weeks, students will receive in-depth training, mentoring and professional development, while being immersed in an active research environment at MSU. They will gain valuable experience in developing their own computationally-focused research project and gain exposure to a wide variety of research problems from different areas of specialty. This project also aims to broaden the pipeline of computational researchers by encouraging participation of underrepresented populations in STEM research, as well as providing early exposure to high performance computing to students from institutions with limited access to HPC resources.This award provides funding for the ACRES (“Advanced Computational Research Experiences for Students”) REU program at Michigan State University (MSU), which provides a unique training environment for undergraduate students. This program is jointly headquartered by two organizations in MSU. The first is the Institute for Cyber-Enabled Research (ICER), who administer MSU’s high performance computing cluster and regularly provide computational training and workshops for MSU students and faculty. The second is the Department of Computational Mathematics, Science, and Engineering (CMSE), founded in 2015, which brings together applied mathematicians and statisticians who create algorithms, with computationally-minded engineers and scientists who can apply these algorithms in diverse contexts. This type of environment breaks down silos and facilitates the spread of ideas between disciplines. Training in interdisciplinary environments is particularly beneficial to undergraduate researchers. It allows students to draw parallels between research concepts early on, such as the modeling of planetary motion around a star and the simulation of atoms in a plasma. It also provides students with exposure to a wide range of research domains in computational science, which could improve students’ enthusiasm for science and students’ retention in the scientific pipeline. In this environment, students will develop a broad understanding of research computing and gain experience in applying domain-specific knowledge to computational modeling problems. This project will also broaden participation in computational science by emphasizing the recruitment of women and students from underrepresented groups, and aim to motivate students to pursue careers in computational fields by fostering an inclusive environment. In addition, the dissemination of the knowledge gained as a result of the students’ research will contribute to advancing the respective scientific fields throughout STEM.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.
在科学和工业领域,应用大规模计算能力来解决问题越来越普遍。因此,至关重要的是让下一代具备满足这一需求所需的技能。这一奖项将资助密歇根州立大学(MSU)面向本科生的暑期研究体验计划,该计划名为“学生的高级计算研究体验”或“Acres”,将为学生提供机会,让他们在各自学科公认的专家的指导下开展计算和数据科学的尖端研究。在为期10周的时间里,学生将接受深入的培训、指导和专业发展,同时沉浸在密歇根州立大学活跃的研究环境中。他们将在开发自己的以计算为重点的研究项目方面获得宝贵的经验,并接触到来自不同专业领域的各种研究问题。该项目还旨在通过鼓励未被充分代表的人群参与STEM研究来拓宽计算研究人员的渠道,并为来自高性能计算资源有限的机构的学生提供早期接触高性能计算的机会。该奖项为密歇根州立大学(MSU)的Acres(为学生提供高级计算研究体验)REU计划提供资金,该计划为本科生提供独特的培训环境。该项目由密歇根州立大学的两个组织联合总部。第一个是网络支持研究所(ICER),负责管理密歇根州立大学的高性能计算集群,并定期为密歇根州立大学的学生和教职员工提供计算培训和研讨会。第二个是计算数学、科学和工程系(CMSE),成立于2015年,将创造算法的应用数学家和统计学家与具有计算意识的工程师和科学家聚集在一起,他们可以在不同的环境中应用这些算法。这种类型的环境打破了孤岛,促进了不同学科之间的思想传播。跨学科环境中的培训对本科生研究人员特别有益。它允许学生在早期的研究概念之间画出相似之处,比如对恒星周围的行星运动进行建模,以及对等离子体中的原子进行模拟。它还为学生提供了接触计算科学的广泛研究领域的机会,这可以提高学生对科学的热情,并使学生在科学管道中保持不变。在这种环境中,学生将发展对研究计算的广泛理解,并获得将特定领域的知识应用于计算建模问题的经验。该项目还将通过强调从任职人数不足的群体中招聘妇女和学生来扩大对计算科学的参与,并旨在通过促进包容性环境来激励学生在计算领域从事职业。此外,学生通过研究获得的知识的传播将有助于在整个STEM中推进各自的科学领域。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Alex Dickson其他文献
Erratum: “Nonequilibrium umbrella sampling in spaces of many order parameters” [J. Chem. Phys. 130, 074104 (2009)]
勘误表:“多阶参数空间中的非平衡伞采样”[J. Phys. 130, 074104 (2009)]
- DOI:
- 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Alex Dickson;Aryeh Warmflash;A. Dinner - 通讯作者:
A. Dinner
The zinc isotope composition of late Holocene open-ocean marine sediments
- DOI:
10.7185/gold2021.7744 - 发表时间:
2022-06 - 期刊:
- 影响因子:0
- 作者:
Alex Dickson - 通讯作者:
Alex Dickson
Creating Maps of the Ligand Binding Landscape for Kinetics-Based Drug Discovery.
为基于动力学的药物发现创建配体结合景观图。
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Tom Dixon;Samuel D. Lotz;Alex Dickson - 通讯作者:
Alex Dickson
People and Policy: Behavioural economics and its policy implications
人与政策:行为经济学及其政策影响
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Alex Dickson;Marco Fongoni - 通讯作者:
Marco Fongoni
The Role of Markets and Preferences on Resource Conflicts
市场和偏好对资源冲突的作用
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Alex Dickson;I. MacKenzie;Petros G. Sekeris - 通讯作者:
Petros G. Sekeris
Alex Dickson的其他文献
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{{ truncateString('Alex Dickson', 18)}}的其他基金
Kinetics-Driven Drug Discovery Using Persistent Homology, Rare-Event Molecular Dynamics and Experimental Data
使用持久同源性、罕见事件分子动力学和实验数据进行动力学驱动的药物发现
- 批准号:
1761320 - 财政年份:2018
- 资助金额:
$ 45.49万 - 项目类别:
Continuing Grant
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