Education and Training
It's not enough for our own faculty and affiliates to adopt a systems-oriented approach to fighting obesity. We need to ensure that professionals around the globe at all career stages are prepared to tackle obesity using a systems science approach.
By educating and training professionals at all levels, the Global Obesity Prevention Center (GOPC) hopes to increase the number of public health researchers applying systems science theories and methods to the obesity epidemic.
OUR STUDENTS AND TRAINEES
We provide trainees from around the world with a range of opportunities designed to motivate them as systems thinkers and researchers, and to give them opportunities to apply their skills at preventing and finding solutions for obesity.
Our trainees receive a combination of formal, course-based learning along with hands-on training in a range of methods and theories—including modeling and simulation techniques—pertinent to systems science and obesity. Students and trainees can also learn about applying systems science to obesity research through a range of activities, including our:
CURRENT OFFERED COURSES
Instructors: Jessica Jones-Smith, Dan Taber, Thomas Glass, Kayla de la Haye and Rahmatollah Beheshti
Description: This online course is designed to introduce students to basic tools of theory building and data analysis in systems science and to apply those tools to better understand the obesity epidemic in human populations. There will also be a lab in which students will use a simple demonstration model of food acquisition behavior using agent-based modeling on standard (free) software (netlogo). The central organizing idea of the course is to examine the obesity epidemic at a population level as an emergent properties of complex, nested systems, with attention to feedback processes, multilevel interactions, and the phenomenon of emergence.
- The epidemiology of obesity across time and place
- Theories to explain population obesity
- The role of environments and economic resources in obesity
- Basic concepts and tools of systems science
- Modeling energy-balance related behaviors in context
- Agent-based models, systems dynamic models and social network models
PREVIOUSLY OFFERED COURSES
PRE-DOCTORAL AND POST-DOCTORAL FELLOWS
We recruit post-doctoral and pre-doctoral fellows with support from collaborating faculty, both at the Johns Hopkins University and from outside institutions. Fellows pursue professional development opportunities at the Bloomberg School for a one-year period. A dual mentorship team is assigned based on research interests. Fellows work with these mentors to identify specific research and academic interests and cultivate desired skill sets. We seek applicants who can work with one or more of the ongoing projects in the Center and who bring additional systems science skills and modeling experience. Trainees also have full access to course offerings both at the Bloomberg School and the Johns Hopkins Whiting School of Engineering.
Each year, the Global Obesity Prevention Center welcomes a select number of visiting scholars to spend a month at Johns Hopkins University, where they can train and participate in relevant research projects. The program offers hands-on experience of how systems science research is integrated to public health and obesity. We offer financial assistance to cover travel and living costs. Visiting scholars may seek additional support from their home institutions and their University sponsoring mentors if they wish to extend their stay.
Our GOPC, the Pittsburgh Supercomputing Center (PSC) and McGill University are partnering up to host the BRIDGE webinar series. BRIDGE is designed to prepare for the next generation of big data analytics, woven into transdisciplinary and intersectoral sciences, policy and innovation. To foster real time learning, the BRIDGE webinar series brings together a new solution-oriented transdisciplinary translational paradigm for the four M's of big data sciences used on both sides of the health and economic divide (Machines, Methods, Models and Matter).
For further information, please see here.