The Duke University Program in Computational Biology and Bioinformatics (CBB) is a predoctoral training program that admits its own students and grants them Ph.D. degrees upon completion. This interdisciplinary program provides rigorous, contextual training in quantitative approaches from computer science, statistics, mathematics, physics, and engineering so that its students are enabled to successfully address contemporary challenges across the biomedical sciences. In addition, CBB trains students to 1) work independently and as part of collaborative teams, 2) conduct research responsibly, with a particular commitment to data sharing and reproducible analysis, 3) effectively communicate science to a broad range of audiences, 4) teach in formal and informal settings, and 5) develop their professional and leadership skills in preparation for their careers. CBB continues to grow and flourish in its unique role on campus of training students to become leaders at the intersection of the quantitative and biomedical sciences. CBB provides high-quality training in both quantitative and biomedical sciences through coursework, research rotations, journal clubs, a weekly seminar that attracts researchers both within and beyond CBB, and hands-on mentoring from enthusiastic advisors, co-advisors, and dissertation committees. This is supplemented by training in responsible conduct of research (and as a new focus, in reproducible data analysis) and teaching, as well as by professional development opportunities that align with each student's individual development plan. CBB has an inclusive and intellectually rich culture of interaction, collaboration, and community, cultivated at its weekly seminar, annual retreat, and social events throughout the year. CBB brings together 55 faculty from 18 departments to conduct cutting-edge research across a wide range of topics in computational biology. Faculty enjoy the collaborative nature of the program, which translates into high participation rates in CBB activities. Their significant publication records, training experience, and available funding make them excellent research mentors. CBB's applicant pool is strong, its selectivity (16%) is excellent, its retention rate (87%) is outstanding, and its average time to the Ph.D. degree is 5.28 years. To date, CBB has produced 37 Ph.D. graduates and has a perfect track record of placing these graduates into excellent positions across academia, industry, and government labs. Approved as a degree-granting Ph.D. program in 2002, CBB first received NIH T32 training grant funding in 2005, and the T32 was renewed in 2011 with 4 funded slots. However, CBB typically admits ~8 new students each year, so the T32 supports just 25% of first- and second-year students. Given the alignment of CBB's mission with broad NIH goals, its unique training role on campus, the high quality of its training, its perfect record of placing its graduates into excellent positions in academia, industry, and government labs, and the growth in size and caliber of its applicants, CBB requests an increase to 8 funded slots. With 8 slots, CBB could admit 10 new students each year, and the T32 would support 40% of first- and second-year students.
The mission of the Duke University Program in Computational Biology and Bioinformatics (CBB) is to train predoctoral students to become leaders at the interdisciplinary intersection of quantitative and biomedical sciences, using sophisticated computational methods to address contemporary challenges across biology and medicine. CBB accomplishes this mission through a thoughtfully designed and regularly evaluated set of program activities; a strong cadre of distinguished, experienced, participative, and collaborative faculty; and an intellectually vibrant community and campus environment-the combination of which ensures that CBB students receive the excellent training necessary to conduct research at the forefront of the rapidly evolving field of computational biology, or to pursue other career interests within the nexus of data-intensive biomedical sciences. Approved as a degree-granting Ph.D. program in 2002, and supported by an NIH T32 training grant since 2005, CBB continues to flourish and innovate, and has a perfect track record of placing its graduates into excellent positions across academia, industry, and government labs.
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