Stanford BSSR Pre-Doctoral Training Program at the Intersection of Data Sciences with Behavioral, Social, and Population Health Research

项目概要/摘要 斯坦福大学BSSR博士前培训计划的使命是数据科学与 行为、社会与人口健康研究是发展跨校园的合作训练 计划提供有才华的博士前学生与先进的专业培训的交叉点， 社会和行为健康科学，社会流行病学，数据科学和人口健康。我们 建立一个新的团队，跨越斯坦福大学校园，包括来自6个学校和11个部门的教师。我们 将提供一个变革性的多学科博士前培训环境，吸引来自 不同的领域（健康和社会心理学，医学社会学，社会流行病学，通信，健康 经济学、商业、教育、法律）和定量学科（计算机科学、信息学、统计学）。 我们计划的毕业生将在自己的科学学科中接受严格的培训， 广泛的专业知识，致力于广泛的创新研究项目，这些项目主要依赖于两个方面的数据 类型：（1）来自移动健康、智能手机和传感器技术的密集或大量纵向数据， 电子健康记录，和/或（2）来自互联网、商业、健康管理的大型复杂数据 记录、大型人口数据库、互联网数据和社交媒体平台、众包和公民 科学数据。博士前学员在他们的研究生学习的第一年或第二年将被录取， 健康心理学，医学社会学，社会/行为流行病学，健康经济学或 另一个社会科学学科。我们正在申请每年5名博士前学生的支持， 培训将持续两年或两年以上。他们将从节目中脱颖而出，彻底了解他们的 自己的基本学科结合先进的专业知识，在尖端的统计和计算 用于分析日益复杂和多维的纵向集合的方法。培训计划 除了全方案的数据外，各组成部分还将包括部门或学科的具体培训 科学部分包括：（1）创新课程，包括专门的量化课程 根据每个学员的经验和背景定制;（2）具有双重指导的研究经验 导师模式（一个学科导师，一个方法导师）;（3）接触团队科学方法 解决问题，包括设计思维，跨学科合作和团队建设;（4） 经验成分，包括斯坦福大学干实验室轮换和短期实习的硅 硅谷公司;（5）知识交流论坛;（6）发展专业人才的许多机会 在赠款写作和合作的技能。BSSR毕业生将有能力进行尖端 研究行为和社会，健康问题，以及预防和治疗干预措施， 有可能降低心、肺、血液和睡眠（HLBS）疾病的风险并改善结局 这些疾病的患者中。

Project Summary / Abstract The mission of the Stanford BSSR Pre-Doctoral Training Program at the Intersection of Data Sciences with Behavioral, Social, and Population Health Research is to develop a cross-campus collaborative training program to provide talented pre-doctoral students with advanced specialized training at the intersections of social and behavioral health science, social epidemiology, data science, and population health. We are building a new team that spans the Stanford campus including faculty from 6 schools and 11 departments. We will provide a transformative multi-disciplinary predoctoral training environment that draws mentors from diverse fields (health and social psychology, medical sociology, social epidemiology, communications, health economics, business, education, law) and quantitative disciplines (computer science, informatics, statistics). The graduates of our program will have rigorous training in their own scientific disciplines, combined with extensive expertise working on a broad range of innovative research projects that rely on data of primarily two types: (1) intensive or voluminous longitudinal data from mHealth, smartphone and sensor technologies or electronic health records, and/or (2) large and complex data from internet, commercial, health administrative records, large population databases, internet data and social media platforms, crowd sourcing, and citizen science data. Predoctoral trainees in their first or second year of graduate studies will be admitted from programs in health psychology, medical sociology, social/behavioral epidemiology, health economics or another social science discipline. We are requesting support for 5 pre-doctoral students per year whose training will last 2 or more years. They will emerge from the program with a thorough understanding of their own fundamental discipline combined with advanced expertise in cutting-edge statistical and computational methods for analyzing increasingly complex and multidimensional longitudinal sets. The training program components will include both department or discipline-specific training in addition to program-wide data science components including: (1) innovative curriculum, including specialized quantitative curriculum customized to the experience and background of each trainee; (2) a mentored research experience with a dual mentor model (one disciplinary mentor, one methodological mentor); (3) exposure to team science approaches to problem solving, including design thinking, cross-disciplinary collaborations, and team building; (4) experiential components, including availability of Stanford dry-lab rotations and short-term internships in Silicon Valley companies; (5) forums for intellectual exchanges; and (6) many opportunities to develop professional skills in grant writing and collaboration. BSSR graduates will have the capability to conduct cutting edge research on behavioral and social, and health issues, as well as prevention and treatment interventions that have the potential to reduce the risks of heart, lung, blood, and sleep (HLBS) disorders and improve outcomes among patients with these disorders.