The InQuBATE Mission
The InQuBATE T32 at the Georgia Institute of Technology will train PhD candidates spanning the biosciences, engineering, and computing to integrate computational models, data analytics, and the experimental study of molecules, cells, and populations. By fostering a quantitative and data-driven mindset, the T32 will train the next generation of thought leaders to identify principles underlying transitions between health and disease in complex living systems spanning microbial communities, developmental pathways, tumor microenvironments and the dynamics of tissue. Overall, InQuBATE will help transform the foundational and applied study of computational- and data-intensive biosciences in the 21st century and prepare diverse trainees for impactful careers across academia and industry.
The primary goal of the InQuBATE T32 training program is to train, mentor, and develop Ph.D. students to reason quantitatively about living systems given uncertainty. Trainees will utilize their skills in the service of harnessing the data revolution to understand mechanisms underlying biological structure and function across spatiotemporal scales from molecules to systems. The scale of projects spans molecular and cellular biosciences, physiology and behavior, and the dynamics of interacting populations (whether of individual cells in a eukaryotic context or of individual microbial organisms as part of biofilms and other aggregates). In doing so, student-driven research advances will be enabled and augmented by advances in computational modeling and data sciences.
The program will combine rigorous training in quantitative models, data analytics, and the study of living systems from molecules to organisms to systems. The training program will combine short- and long-form coursework, collaborative research experiences, and professional development initiatives to prepare for dynamic careers in the biosciences spanning academia, industry and government, including the following objectives:
- Integrate rigorous computational and data science methods into core biomedical sciences training,
- Catalyze research discoveries in computational and data-enabled biosciences,
- Establish a diverse pipeline of in-demand bioscientists for industry, government and academia,
- Broaden participation of a vital workforce through targeted recruitment, mentoring and retention,
- Build a reproducible template for interface training in the biosciences,
- Support PhD retention and completion by trainees with a median 5-6 year time to degree.
- Evaluate the performance of the program and students to refine and refocus efforts, and
- Report and disseminate the research and training discoveries to the broader community.
The InQuBATE faculty trainers are committed to build upon the successes of established and recently launched interdisciplinary graduate programs to foster an innovative and welcome environment at the interface of the biomedical sciences, bioengineering, and data analytics.