T32 Computational Approaches to Diabetes and Metabolism
T32 Training Program in Computational Approaches to Diabetes and Metabolism Research
The University of Utah is the recipient of a Computational Approaches to Diabetes and Metabolism Research T32 Training Grant.
The grant funds research training of 3 predocs and 2 postdoc positions in biomedical informatics. Applications do not follow the general admissions timelines and open throughout the year. Please contact the Academic Program Manager before starting an application to confirm funding availability.
This training grant is designed to cross-train a cadre of predoctoral and postdoctoral trainees in the computational and mathematical sciences and in the biological basis of diabetes and obesity. These bioinformatics scientist trainees will gain the expertise and leadership skills to apply computational and mathematical methods to complex biological questions that will ultimately impact the prevention, treatment, and outcomes of people with diabetes and related metabolic diseases. This training program will consist of a combination of mentored research and career development training, coursework, and extensive interactions with faculty and trainees across campus and beyond.
Each trainee will be required to have at least one computational and one biological mentor to serve as the foundation of their mentoring team. Computational Mentors can be pulled from the broad fields of Genomics, Clinical Informatics, Big Data Analytics, Mathematical Biology, Data Visualization and Scientific Computing, and Structural Computing. Biological Mentors can be pulled from research themes of Adipose Biology and Insulin Control, Metabolic Mechanisms, and Diabetic Complications and Vascular Biology. Mentors for this training Program and application details available upon request. Please contact the Academic Program Manager.
This training program makes special efforts to recruit individuals from underrepresented racial and ethnic groups, individuals with disabilities, and those from economically, socially, culturally or educationally disadvantaged backgrounds, into careers in biomedical informatics. The positions are for US citizens and permanent residents.