University of Pennsylvania has trained computational genomicists for the past 20 years supported by the NHGRI T32 program, training 52 predoctoral and 13 postdoctoral trainees the majority of whom have gone on to careers in research and development. Here we propose to continue our Computational Genomic Training program with eight predoctoral and two postdoctoral trainees focused on the theme of Data Science and Machine/Statistical Learning methods as applied to genomics data. Our training program concentrates on a rigorous course-based curriculum supported by courses in multiple graduate groups. In addition, our training also involves 13-16 hours of Responsible Conduct of Research (RCR) and Scientific Rigor and Reproducibility (SRR) training, Individual Development Plan, and utilization of Electronic Notebooks and code repositories. Research training is enhanced by a dual mentorship model whenever possible. Our program is supported by a greater genomics training program consisting of three NHGRI T32 programs in Computational Genomics (this program), Genomic Medicine, and ELSI, as well as a NHGRI R25 Diversity Action Plan (DAP). In particular, the DAP program recruits URM undergraduate and postbacc trainees focused on the Greater Philadelphia Area whose many institutions serve the urban URM population. This vertical regional integration will allow us to develop a regional pipeline of URM students with undergraduate research experience in genomics. Our program consists of 31 trainers of which 14 are female scientists and 2 are URM scientists. Twenty one of our 31 trainers have an active computational genomics research program. The expertise of the trainers span disease genomics, genomic technologies, multidimensional statistics, algorithms, data sciences, and machine learning. Our training environment is enhanced by key facilities including large biobanks, high-throughput genomics core, high-performance computing core, and a unique immersive data visualization facility. Penn overall hosts more than 60 NIH training programs with strong institutional administrative support for managing the training programs including an Office of Biomedical Postdoctoral Programs, Office of Diversity and Inclusion, combined Biomedical Graduate Studies, among others. Success of our training program will help train the next generation of genomic workforce in the skills and knowledge necessary to apply state-of-art computational techniques to genomics and develop new techniques for novel genomic data.
This project is to create a training program for graduate students and post-graduate students as well as MD/PHD students to acquire skills to apply Data Science and Artificial Intelligence techniques to genomics of human diseases. Success of the program will contribute to training the next generation of biomedical workforce in the application of state-of-art computation to genomics data.
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