Integrated Interdisciplinary, inter-university PhD Program Computational Biology (T32)

综合跨学科、跨大学博士课程计算生物学（T32）

• 批准号: 9978582
• 负责人: Ivet Bahar
• 金额: $ 27.42万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-04-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9978582
• 关键词: Computational Biology; Doctor of Philosophy; Universities; programs

Project Summary Computational biology has in a few decades transformed from a specialized discipline to one of the most important enabling technologies behind modern biomedical research. There is no corner of biomedicine today that does not require the development and use of advanced computational methods, and the resulting models, algorithms, and software have become an essential component of new advances in biotechnology and the biomedical discovery they enable. High-throughput imaging, high throughput sequencing, metabolomics, structure modeling, network modeling, genetic association testing, and a host of other transformative technologies today depend critically on advanced computational technologies and on researchers able to design and innovate in this area. The need for advances in computation is only accelerating, as the data deluge becomes ever more acute and dealing with terabyte to petabyte datasets becomes the norm for even small laboratories doing routine studies. The Carnegie Mellon University – University of Pittsburgh PhD Program in Computational Biology (CPCB) was created to meet the field's pressing need for experts trained in computational biology. The program aims to prepare the future leaders of computational biology: research scientists with deep knowledge of computational theory, biological and physical sciences, and a growing body of specialized interdisciplinary knowledge at the intersection of these areas. To accomplish this, the program leverages the shared strengths of its two host institutions, collectively world leaders in computer science, engineering, and medical research with long track records of innovation in computational biology research and education. The training program includes an innovative curriculum covering fundamentals of computational biology, and a large body of advanced elective coursework spanning many areas of computational biology research. Thesis research takes place in any of numerous laboratories at the cutting edge of computational and data-driven biology. Coursework and thesis research are supplemented by mechanisms to facilitate student success, promote professional development, encourage responsible conduct of research, and aid in recruiting and retaining underrepresented groups. We seek to renew support for a select subset of students in the broader CPCB graduate program. It will provide the most promising students with two years of research support, added resources, and flexibility to pursue the most innovative research. Entering its 14th year, the program’s trainees have a proven track record of success. Graduates have attained faculty positions, postdoctoral positions in top research labs, and research positions at top companies in biomedical and health-related companies. The renewal proposal includes new innovations in curriculum design, professional development training, and student participation in program governance. !

项目总结