RII-BEC: Training Diverse Scholars in Data Science to Understand the Brain and Behavior

RII-BEC：培训数据科学领域的多元化学者以了解大脑和行为

• 批准号: 2225805
• 负责人: Timothy Vickery
• 金额: $ 99.99万
• 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: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2225805&HistoricalAwards=false
• 关键词: RII; BEC; Training; Diverse; Scholars

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). This project aims to serve the national interest by developing scholars skilled in data science and statistics to understand behavior. Advances in behavioral and neuroscientific research over the last decade have led to the production of large datasets ranging in scale from activity in single neurons to social behavior in large groups. Processing and distilling this data – to understand the mind and brain, and to develop ways to address questions of societal importance – is of national importance and requires individuals with interdisciplinary training in data science, statistics, and psychology/neuroscience. The COVID-19 pandemic led to a decrease in research opportunities that has disproportionately affected individuals from underrepresented groups, making it more difficult for them to pursue STEM careers in understanding behavior and the mind. To this effect, this project aims to create a new, two-year post-baccalaureate program in data science and psychology, designed to provide intensive training for careers in academia and/or industry. This project intends to develop the next generation of interdisciplinary researchers with skills in both data science and psychology/neuroscience, specifically targeting those from underrepresented groups. The significance of this project is the production of a highly skilled and diverse workforce in an increasingly important domain that spans basic science and industry.The goal of this project is to develop a bridge program that provides individuals from underrepresented groups with two years of training to prepare them for STEM careers in academia and/or industry. The training scope will be in three domains. First, participants will engage in active research mentored by a faculty member with expertise in behavior and/or neuroscience. This research will culminate in multiple deliverables, including a thesis-level peer-reviewed publication that will bolster both doctoral and industrial career opportunities. Second, participants will enroll in curriculum specific to this program, with courses focused on developing skills in data science that can be applied to understanding behavior and the brain. Third, participants will engage in professional development via a group seminar along with clearly defined, accessible pathways to ensure progress towards their chosen career. The outcome of this training will be a set of tangible skills and experiences for the student, which will increase their competitiveness in the workplace and provide economically important skills to the academic and industrial marketplace.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.

该奖项的全部或部分资金根据《2021 年美国救援计划法案》（公法 117-2）提供。该项目旨在通过培养精通数据科学和统计学的学者来理解行为，从而服务于国家利益。过去十年中行为和神经科学研究的进步导致了大型数据集的产生，其规模从单个神经元的活动到大型群体的社会行为。处理和提炼这些数据——以了解思想和大脑，并找到解决具有社会重要性的问题的方法——具有国家重要性，需要接受过数据科学、统计学和心理学/神经科学跨学科培训的个人。 COVID-19 大流行导致研究机会减少，这对代表性不足群体的个人造成了不成比例的影响，使他们更难从事理解行为和思想的 STEM 职业。为此，该项目旨在创建一个新的、为期两年的数据科学和心理学学士学位后课程，旨在为学术界和/或工业界的职业提供强化培训。该项目旨在培养具有数据科学和心理学/神经科学技能的下一代跨学科研究人员，特别针对那些来自代表性不足的群体。该项目的意义在于在跨越基础科学和工业的日益重要的领域培养高技能和多样化的劳动力。该项目的目标是开发一个桥梁计划，为来自代表性不足群体的个人提供两年的培训，为他们在学术界和/或工业界的 STEM 职业做好准备。培训范围将分为三个领域。首先，参与者将在具有行为和/或神经科学专业知识的教员的指导下进行积极的研究。这项研究最终将产生多项成果，包括一篇论文级的同行评审出版物，该出版物将增加博士和工业职业机会。其次，参与者将报名参加该项目的特定课程，课程重点是培养可应用于理解行为和大脑的数据科学技能。第三，参与者将通过小组研讨会进行专业发展，并提供明确定义的、可访问的途径，以确保他们在所选职业方面取得进展。此次培训的成果将为学生提供一套切实的技能和经验，这将提高他们在工作场所的竞争力，并为学术和工业市场提供经济上重要的技能。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标准进行评估，被认为值得支持。