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. !
Biomedical research has become a data-intensive field that depends on researchers with sophisticated knowledge of both computational and biomedical sciences. By training a core of exceptionally talented students in these skills, the current program has contributed to training the next generation of leaders in computational biology to help advance medical treatments that now critically depend on computational innovation, such as medical image analysis, personalized and genomic medicine, and modern drug design. Building on a track record of success, the proposed renewal would improve training by enabling the development of new courses at the cutting edge of the field, offer further opportunities for professional development, improve recruitment and retention of students from underrepresented groups, and further engage students in program governance. !
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