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Beginnings: Introducing Molecular Modeling Experiences to Underrepresented Students

Beginnings: Introducing Molecular Modeling Experiences to Underrepresented Students
起点:向代表性不足的学生介绍分子建模经验
批准号:
2322496
负责人:
Mai Zahran
金额:
$99.87万
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-10-01 至 2026-09-30

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项目成果

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中文摘要
翻译
分子建模在生物技术和药物发现中起着关键作用。为了促进这一领域的创新,生物技术公司拥有一支多样化和训练有素的员工队伍至关重要。扩大进入这一领域的途径之一是为来自代表性不足背景的本科生提供行业水平的知识。学生在实践中学习的体验式学习机会是扩大这些群体参与的一种特别有效的方式,因为它提供了工业所需的技术技能。地方公共学术界和工业界之间的伙伴关系将通过为未来的科学家提供更好的培训来促进科学进步,并通过扩大合格的生物技术工作人员的数量来促进国家卫生。该项目旨在使未被充分代表的少数民族学生能够积极参与生物技术领域,并将他们独特的观点带到桌面上。通过使STEM劳动力多样化,目标是加强创新,培养创造力,并为全球问题制定更具包容性的解决方案。向代表性不足的学生介绍分子建模经验(immersion)的倡议旨在促进拉瓜迪亚社区学院和纽约城市理工学院之间的跨部门合作伙伴关系,这两个学院都是纽约城市大学(CUNY)系统;以及总部位于纽约的分子建模软件的生物技术行业领导者Schrödinger。目标是通过将行业驱动的问题纳入课堂,并随后参与Schrödinger实习计划,为本科生分子建模职业做好准备,然后导致专业职业。为了实现这一目标,项目团队将以多阶段方法提供体验式学习。首先,在课堂上,学生将学习与生物技术相关的分子建模概念。第二,动手培训将提供说明如何使用分子建模工具一步一步的格式。第三,将在Schrödinger提供带薪实习机会,学生将在那里边做边学,同时还将研究与行业相关的问题,这将使他们在就业市场上更具竞争力。预期的结果是训练有素和多样化的学生,他们为计算机生物技术的职业生涯做好了充分的准备。该项目与由NSF TIP和EDU董事会资助的NSF ExLENT计划保持一致,因为它旨在为来自不同专业和教育背景的个人提供体验式学习机会,以增加他们对新兴技术领域职业道路的兴趣和机会。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。
英文摘要
Molecular modeling plays a pivotal role in biotechnology and drug discovery. To foster innovation in this field, it is crucial for biotechnology companies to have a diverse and well-trained workforce. One way to expand access to this field is by equipping undergraduate students from underrepresented backgrounds with industry-level knowledge. Experiential learning opportunities, in which students learn-by-doing, is a particularly effective way to broaden participation of these groups because it provides technical skills needed by industry. A partnership between local public academia and industry will promote the progress of science by providing better training to future scientists and advance national health by broadening the pool of well-qualified biotechnology workforce members. This project aims to empower underrepresented minority students to actively participate in the biotechnology field and bring their unique perspectives to the table. By diversifying the STEM workforce, the goals are to enhance innovation, foster creativity, and develop more inclusive solutions to global problems.The initiative Introducing Molecular Modeling Experiences to underRepresented StudEnts (IMMERSE) aims to promote a cross-sector partnership between LaGuardia Community College and the New York City College of Technology, both of the City University of New York (CUNY) system; and Schrödinger, a biotechnology industry leader in molecular modeling software, headquartered in New York City. The goal is to prepare undergraduate students for molecular modeling careers by incorporating industry-driven problems to the classroom, and subsequent participation in a Schrödinger internship program, that then leads to specialized careers. To achieve this goal, the project team will provide experiential learning in a multistage approach. First, in the classroom, students will be taught molecular modeling concepts relevant to biotechnology. Second, hands-on training will be provided to illustrate how to use the molecular modeling tools in a step-by-step format. Third, paid internship opportunities at Schrödinger will be provided, where students will learn-by-doing, while also working on industry-relevant problems that will make them more competitive in the job market. The expected outcome is highly trained and diverse students who are well-equipped for a career in computational biotechnology. This project aligns with the NSF ExLENT Program, funded by the NSF TIP and EDU Directorates, as it seeks to support experiential learning opportunities for individuals from diverse professional and educational backgrounds to increase their interest in, and their access to, career pathways in emerging technology fields.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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