ABSTRACT
This new T32 research training program will provide postdoctoral fellows training in sleep and circadian
research. It builds on a prior highly successful postdoctoral training program and is part of a comprehensive
succession plan for T32 leadership at the University of Pennsylvania. The fellows can have PhD, MD, VMD, or
MD/PhD degrees. The program provides support for each fellow for up to three years to provide the training they
require to reach the next level of career advancement. The program is broad in scope. It is organized into specific
tracks, each of which has a number of faculty who can act as mentors. The specific tracks are as follows: a)
basic research in sleep and circadian mechanisms; b) clinical/translational research in sleep and its disorders;
c) personalized medicine approaches that include development of biomarkers, genetics of complex traits, and
big data approaches using electronic health records (EHR). Each track has relevant didactic courses and there
are multiple Masters degree programs that fellows can pursue. There are also organized programs to teach
academic survival skills—grant writing, giving scientific talks, and negotiating for a position. The program also
offers the ability to collaborate with faculty at other institutions including Jackson Laboratory (mouse genetics),
Geisinger Clinic (big data, genetics), and Kaiser Southern California (big data approaches). Penn developed the
first medical-school wide center to facilitate sleep/circadian research in 1991 and the first multidisciplinary Sleep
Medicine Division in 2001. These developments have led to Penn training the largest number of successful
investigators in sleep/circadian research of any institution in the world. The program takes advantage of the
infrastructure that has been developed at Penn over the past 30 years for research training. This includes the
Office of Biomedical Postdoctoral Programs (BPP), the Master of Science in Clinical Epidemiology, the Master
of Science in Translational Research, and the Master of Science in Biomedical Informatics.