CyberTraining: CIP: Training and Developing a Research Computing and Data CI Professionals (RCD-CIP) Community
CyberTraining: CIP: Training and Developing a Research Computing and Data CI Professionals (RCD-CIP) Community
批准号:
2230127
负责人:
Mary Thomas
金额:
$670.2万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-01 至 2027-08-31
中文摘要
今天的科学和工程研究界是跨学科的性质和不断发展超越单一学科的界限,往往不仅需要深度,而且跨越这些学科的知识广度。特别是,科学对先进的计算资源和专业人员的需求日益增长,他们可以作为科学研究和先进计算基础设施或网络基础设施(CI)之间的桥梁。该项目通过培训和单独指导一批跨学科研究CI专业人员(IDR-CIP)来认识和支持这些复杂的需求,这些专业人员使用获得的技术能力和软技能与研究团队成功合作。IDR-CIP学员来自社区,包括:领域科学家,跨学科研究专业人员,教师和学生。IDR-CIP学员被嵌入到研究项目中,使他们有机会发展CI技能,从而成为更大社区的一部分。培训计划使用以下核心活动产生经验丰富的CIP,包括:制定个性化的培训计划;进行培训周期,支持新的,现有的和返回的学员;将学员嵌入参与机构的项目和计划;指导科学研究项目匹配;赞助教师研究员计划;通过赞助IDR-CIP学员参与促进社区;并倡导受训人员成为CIP职位的全额资助人员。该项目的成果包括定义新的IDR-CIP劳动力职业道路,反映其对研究企业的重要性,并有可能影响NSF生态系统中的研究方式。招聘过程积极接触各种代表性不足的社区,从而推进NSF目标的一个重要方面,即扩大科学和工程的参与。拥有这样的网络基础设施专业人员来支持研究人员及其日益复杂的计算需求,对我们国家的竞争力至关重要。2022年,NSF将增长融合研究列为其十大创意之一。融合研究将专家联系起来,他们共同解决需要广泛而多样化的知识,方法,专业知识,科学学科和CI能力的问题。然而,缺乏跨学科的网络基础设施(CI)专业人员(CIP)是前进的障碍。该项目的主要目标是通过开发一个与每个受训者的能力和背景相一致的培训计划来减轻这一障碍。该项目对培训CIP劳动力的教学挑战的一个重要贡献是围绕四个主要要素阐明和组织培训:1)招聘&培训:战略性地接触新社区;制定灵活的培训周期,支持新的,现有的和返回的学员;为CIP培训计划创建精选的培训材料集; 2)科学&工程项目匹配和指导:基于CIP技能,确定S& E项目,并将每个CIP与导师;将学员连接到NSF ACCESS计算科学支持网络(CSSN); 3)科学研究咨询:指导和跟踪学员过渡到独立顾问阶段;通过确定适当的职业道路,促进CIP学员过渡到全职专业职位; 4)培养CIP社区:通过会议和社交媒体连接计划CIP学员;促进与其他CIP和网络培训计划的互动;赞助学员成为培训师并加入其他HPC社区。该培训计划填补了CI研究生态系统中的一个重要空白,并通过创建具有适当职称和职业途径的新CIP职位,以及将CIP过渡到完全资助的工作人员职位,帮助实现融合研究。CIP培训计划将提高新社区对CI资源的认识,为他们更多地融入研究项目提供途径,并支持CI的长期战略发展。CIP培训材料将通过一个公共网站公开提供给NSF网络工作人员。作为拟议的合作和推广的结果,该计划将影响成千上万的用户,并帮助发展下一代的CIP研究队伍。该奖项反映了NSF的法定使命,并已被认为是值得通过评估使用基金会的知识价值和更广泛的影响审查标准的支持。
英文摘要
Today’s science and engineering research community is interdisciplinary in nature and continually evolving beyond the boundaries of single disciplines, often requiring not only depth but also breadth of knowledge across those disciplines. In particular, science has a growing need for advanced computing resources and professionals who can serve as a bridge between the worlds of scientific research and advanced computing infrastructure, or cyberinfrastructure (CI). This project recognizes and supports these complex needs by training and individually mentoring a cohort of Interdisciplinary Research CI Professionals (IDR-CIPs) who use acquired technical competencies and soft skills to work successfully with research teams. The IDR-CIP trainees are drawn from communities including: domain scientists, interdisciplinary research professionals, faculty, and students. IDR-CIP trainees are embedded into research projects, giving them the opportunity to develop CI skills, and as a result, become part of a larger community. The training program produces experienced CIPs using the following core activities, including: developing individualized training programs; conducting training cycles that support new, current, and returning trainees; embedding trainees within the participating institution’s projects and programs; mentoring scientific research project matching; sponsoring a Faculty Fellows program; fostering communities through sponsoring IDR-CIP trainee participation; and advocating for trainees to become fully funded staff in CIP positions. An outcome of this project includes the definition of new IDR-CIP workforce career paths that reflect their importance for the research enterprise and has the potential to impact how research is done in the NSF ecosystem. The recruitment process actively reaches out to a variety of underrepresented communities, thereby advancing an important aspect of NSF’s goal to broaden participation in science and engineering. It is vital for the competitiveness of our nation to have such cyberinfrastructure professionals available to support researchers and their increasingly complex computational needs.In 2022, the NSF named Growing Convergence Research as one of their 10 Big Ideas. Convergence research interconnects experts who work together to solve problems that require a broad and diverse set of knowledge, methods, expertise, scientific disciplines, and CI capabilities. However, the lack of interdisciplinary cyberinfrastructure (CI) professionals (CIPs) presents a barrier to advancement. This project's main goal is to mitigate this barrier by developing a training program that aligns with the competencies and backgrounds of each individual trainee. An important contribution of this project to the pedagogical challenge of training a CIP workforce is to articulate and organize training around four major elements: 1) Recruitment & Training: strategically reach out to new communities; develop a flexible training cycle that supports new, current and returning trainees; create a curated collection of training materials for CIP training programs; 2) Science & Engineering Project Matching and Mentoring: Based in CIP skillset, identify S&E projects and match each CIP with a mentor; connect trainees to the NSF ACCESS Computational Science Support Network (CSSN); 3) Scientific Research Consulting: Mentor and track trainees as they transition to an independent consultant phase; facilitate CIP trainee transition to full time professional positions by identifying appropriate career paths; 4) Fostering a CIP Community: connect program CIP trainees through meetings and social media; foster interactions with other CIP and CyberTraining programs; sponsor trainees to become trainers and to join other HPC communities. This training program fills an important gap in the CI research ecosystem and helps enable convergence research through the creation of new CIP positions with appropriate job titles and career pathways, and transition CIPs to fully funded staff positions. The CIP training program will raise awareness of CI resources in new communities, provide an avenue for their increased integration into research projects, and support long-term strategic CI development. CIP training materials will be publicly available to reach beyond the NSF cyber workforce via a public website. As a result of the proposed collaboration and outreach, this program will impact thousands of users and help develop the next generation of the CIP research workforce.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.
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CyberTraining: Implementation: Small: Developing a Best Practices Training Program in Cyberinfrastructure-Enabled Machine Learning Research
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批准号:2017767
-
项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2020
-
负责人:Mary Thomas
-
依托单位:
NMI: Collaborative Proposal: Middleware for Grid Portal Development
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批准号:0453592
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项目类别:Cooperative Agreement
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资助金额:$0.0万
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财政年份:2004
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负责人:Mary Thomas
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依托单位:
NMI: Collaborative Proposal: Middleware for Grid Portal Development
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批准号:0330652
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项目类别:Cooperative Agreement
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资助金额:$58.78万
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财政年份:2003
-
负责人:Mary Thomas
-
依托单位:
国内基金
海外基金
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