Program Requirements

Students accepted into the Training in Advanced Data Analytics and Computational Sciences to End Drug-Related Harms (TADA) Program are required to participate in all required TADA training opportunities, including:

Two-semester TADA course with lab

  • The two-semester course sequence will embed data science methods into the social and behavioral science (SBS) research lifecycle for substance use disorders (SUD).
  • The courses will introduce advanced data analytics in the framework of SBS theory to both link SBS trainees to data science and also to link data science trainees to SBS research and data challenges.
  • This two-semester sequence (3 credits/semester) will be structured in a series of five modules, each of which will explore one SBS theory that has been used to study or intervene in SUD-related health outcomes, and examine how a particular advanced data science method could strengthen related research or interventions

GDPH/CDC summer research rotation

  • Summer research rotations at the Georgia Department Of Public Health and the US Centers for Disease Control


  • TADA-certified Mentor Team
    TADA co-directors will match each trainee with 2 mentors:
    One with substantive expertise in SBS approaches to studying or intervening in SUD-related harms, the other with expertise in an advanced data science methods.

  • TADA training in menteeship

Two-semester mentored Emory Graduate Research Assistant position

  • In addition to coursework, for four semesters, all students will serve as Graduate Research Assistants (GRAs) with a faculty mentor to gain hands-on SBS research experience.

Regularly scheduled meetings to advance scholarship:

  • Bi-weekly dissertation workshops
  • Monthly journal club
  • Annual research symposium
  • Bi-annual distinguished visitor lecture

$5,000 dissertation grant

  • Each funded TADA trainee will receive $5,000 to support dissertation-related research expenses.

Students must also select a specific methodological track in which to focus coursework and research rotations including, but not limited to:

  • Geospatial Analysis
  • Machine Learning
  • Genetic and Environmental Influences and Interactions
  • Social networks