Big Data to Knowledge Training Program

 描述(由申请人提供)：生物学、生物统计学、计算机科学、流行病学、遗传学、数学、营养学、物理学和天文学、统计学和运筹学；信息与图书馆学学院和药学学院；北卡罗来纳大学教堂山分校(以下简称北卡罗来纳大学)生物信息学和计算生物学、遗传学和分子生物学以及毒理学课程，要求为六名学员提供五年的跨学科“大数据到知识”培训计划的支持。该项目将来自四所学校和文理学院的教职员工和学生团结在一所杰出的研究型大学，该大学坐落在许多大数据产业的发源地研究三角地带。这6名学员将组成一个多学科的队列，平均来自生物医学领域、计算机科学和信息学领域以及数学和统计领域。该提案寻求将学员家庭系博士课程的严密性和深度与大数据生物医学科学目前和未来职业所必需的、具体的说教、经验和团队科学方法相结合。BD2K学员将在各自的学科领域攻读博士学位，同时参与本申请提供的大数据科学方面的强化和补充培训。我们BD2K大数据培训计划的共同特点是，所有受支持的学员，以及在不同程度上利用我们课程的所有研究生，将为他们剩余的职业生涯做好准备和装备，在生物医学科学的背景下开发新的大数据方法，并参与大数据工具的发展和应用于生物医学科学。

 DESCRIPTION (provided by applicant): The Departments of Biology, Biostatistics, Computer Science, Epidemiology, Genetics, Mathematics, Nutrition, Physics and Astronomy, and Statistics and Operations Research; the School of Information and Library Science and the School of Pharmacy; and the Curriculums in Bioinformatics and Computational Biology, Genetics and Molecular Biology, and Toxicology, at the University of North Carolina at Chapel Hill (henceforth UNC-CH or Carolina) request five years of support for six trainees in an interdisciplinary "big data to knowledge" training program. This program unites faculty members and students from four schools and the College of Arts and Sciences in an outstanding research university nestled in the Research Triangle, home to many Big Data industries. The 6 trainees will constitute a multidisciplinary cohort drawn evenly from the biomedical science domain, computer science and informatics domain, and the mathematics and statistics domain. The proposal seeks to combine rigor and depth of a trainee's home Departmental PhD program interwoven with a blend of didactic, experiential, team-science approaches necessary for, and specific to, present and future careers in Big Data biomedical science. The BD2K trainees will pursue the PhD in their respective disciplinary domain, while simultaneously engaging in the enhanced and supplemental training in Big Data Science provided by this application. The common trait aimed for in our BD2K Big Data training program is that all supported trainees, and to variable extent all graduate students who take advantage of our curriculum, will be poised and equipped for the remainder of their careers to develop new methods of Big Data in the context of biomedical science, and to participate in the evolution of Big Data tools development and application to biomedical science.