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

项目摘要 在几十年的时间里，计算生物学已经从一门专门的学科转变为 现代生物医学研究背后的重要使能技术。今天没有生物医学的角落 这不需要开发和使用先进的计算方法，以及由此产生的模型， 算法和软件已成为生物技术新进展的重要组成部分 它们使生物医学发现成为可能。高通量成像、高通量测序、代谢组学、 结构建模、网络建模、基因关联测试以及许多其他变革性 当今的技术在很大程度上依赖于先进的计算技术和能够 在这个领域进行设计和创新。对计算进步的需求只会加速，因为数据 洪灾变得越来越严重，处理从TB到PB的数据集成为常态 进行常规研究的小型实验室。 卡内基梅隆大学-匹兹堡大学计算生物学博士项目 它的创建是为了满足该领域对受过计算生物学培训的专家的迫切需求。该计划旨在 培养未来的计算生物学领导者：拥有深厚计算知识的研究科学家 理论、生物和物理科学，以及不断增长的专业跨学科知识 这些区域的交叉点。为了实现这一点，该计划利用其两个主机的共享优势 机构，统称为计算机科学、工程和医学研究的世界领先者 计算生物学研究和教育领域的创新记录。该培训计划包括 涵盖计算生物学基础的创新课程，以及大量的高级选修课 课程涵盖计算生物学研究的多个领域。论文研究在任何一个地方进行 众多处于计算和数据驱动生物学前沿的实验室。课程和论文 研究得到了促进学生成功的机制的补充，促进了专业发展， 鼓励进行负责任的研究，并帮助招募和留住代表性不足的群体。 我们寻求继续支持更广泛的CPCB研究生课程中选定的一部分学生。会的 为最有前途的学生提供两年的研究支持、额外的资源和灵活性 从事最具创新性的研究。进入第14个年头，该项目的实习生已经有了良好的记录 成功之路。毕业生已获得教师职位、顶级研究实验室的博士后职位，以及 在生物医药和健康相关公司的顶尖公司担任研究职位。续期方案 包括在课程设计、专业发展培训和学生参与 计划治理。 好了！

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. !