BU Summer Institute for Research Education in Biostatistics and Data Science

摘要 波士顿大学(BU)提出了一个全面的计划，名为`波士顿大学暑期学院 《生物统计与数据科学研究教育》(BU SIBS)，包括生物统计分析， 流行病学、传染病模型、临床试验的设计和分析、统计基因组学以及 数据科学框架内的统计计算。该结构包括在线模块，位于五个- 一周的入驻计划，然后是一个有指导的团体研究项目的额外远程工作。这个 严格的课程中穿插着当前的例子，强调生物统计学与特别是 强调生物医学大数据、机器学习方法和高性能计算。BU SIBS是 旨在吸引和吸引不同群体的本科生、新近毕业的学生和早期研究生 来自美国各地。我们的教职员工热情而专注，我们的特邀演讲者也是如此。 来自学术界和工业界的数据科学家、生物统计学家、流行病学家和内科科学家。手- 使用国家心肺血液研究所(NHLBI)Framingham的教学数据集进行分析 心脏研究和杰克逊心脏研究，以及相关的新冠肺炎和结核病的例子，加强技能 在计算、数据可视化、统计和计算建模以及对调查结果的解释方面 加深对卫生不平等这一中心主题的了解。典型的日程表将包括一个上午 结合R编程示例和主动学习练习进行授课。午餐后在BU餐厅就餐 设施学员将返回计算机教室完成与以下内容相关的简短作业 讲课内容或专注于新的计算技能(SAS/Linux)或从事小组研究项目。这个 研究项目将跨越整个项目，并将深入吸引学生在一个内容领域。使用 研究导师，学生将确定一个研究问题，制定分析计划和建议， 进行分析，并综合和展示结果。每天的日程表中将穿插着客人 演讲者和现场访问(例如，弗雷明翰心脏研究)。关于职业道路和毕业生的多个会议 学校也包括在内。BU的大力机构支持提供50%的学费奖学金，教学 助教和基础设施，以支持项目期间学生生活的方方面面。BU已经跑了一个夏天 自2004年起在生物统计研究所(BU SIBS)工作。我们的记录非常好。我们成功地保持了关注 高达92%的BU SIBS校友(2004-2020年)和~65%的以前的参与者已加入 生物统计学或相关学科的研究生课程，或在该领域找到工作。我们的经验是 我们之前的BU SIBS计划将使我们能够快速实施新的BU SIBS计划，保持久经考验的 我们过去计划的各个方面，同时引入了新的元素，包括数据科学框架、扩展的 传染病模块，更强的健康不平等重视，以及更深入的研究经验。

ABSTRACT Boston University (BU) proposes a comprehensive program entitled the `Boston University Summer Institute for Research Education in Biostatistics and Data Science' (BU SIBS) that includes biostatistical analysis, epidemiology, infectious disease modeling, design and analysis of clinical trials, statistical genomics, and statistical computing within a data science framework. The structure includes online modules preceding a five- week in-residence program followed by additional remote work on a mentored group research project. The rigorous curriculum is interspersed with current examples highlighting the relevance of biostatistics with particular emphasis on biomedical big data, machine learning approaches, and high performance computing. BU SIBS is designed to interest and engage a diverse group undergraduates, recent graduates and early graduate students from across the US. Our faculty is enthusiastic and committed, as are our guest speakers who are practicing data scientists, biostatisticians, epidemiologists, and physician-scientists from academia and industry. Hands- on analyses with teaching data sets from the National Heart, Lung, and Blood Institute's (NHLBI) Framingham Heart Study and Jackson Heart Study, along with relevant COVID-19 and tuberculosis examples, reinforce skills in computing, data visualization, statistical and computational modeling, and interpretation of findings while deepening exposure to a central theme of health inequities. The typical daily schedule will include a morning lecture with incorporated R programming examples and active learning exercises. After lunch at the BU dining facilities participants will return to the computer classroom to complete short assignments either relevant to the lecture content or focused on new computing skills (SAS/Linux) or to work on the group research project. The research project will span the entire program and will deeply engage students in a content area. Working with a research mentor, the students will determine a research question, develop an analysis plan and proposal, conduct the analysis, and synthesize and present results. The daily schedule will be interspersed with guest speakers and site visits (e.g. to the Framingham Heart Study). Multiple sessions on career paths and graduate school are also included. Strong institutional support from BU provides a 50% tuition scholarship, teaching assistants, and infrastructure to support all aspects of student life during the program. BU has run a Summer Institute in Biostatistics (BU SIBS) since 2004. Our track record is very strong. We successfully maintain follow up of 92% of our BU SIBS alumni (2004-2020) and ~65% of our prior participants have either entered into graduate programs in biostatistics or a closely related discipline or taken jobs in the field. Our experience with our prior BU SIBS programs will enable us to rapidly implement a new BU SIBS program, maintaining proven aspects of our past program while introducing new elements including a data science framework, an expanded infectious disease module, stronger health inequities emphasis, and a more in depth research experience.