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Skills & Workforce Development

Training and expanding the AI/ML-biomedical research workforce.

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Overview of the Skills & Workforce Development Module

The overall objective of the AI-READI Skills and Workforce Development Module is to develop and deploy training and career development activities for individuals who will effectively contribute to translational AI research, particularly in the biomedical/clinical domain.

To achieve this objective, our module is engaged in the following aims:

  • Design and implement a structured, yearlong mentored research internship program to facilitate exposure to skills in AI and data science for post-baccalaureate students, medical students, pre-doctoral students, postdoctoral fellows, and other health care professionals wanting to gain AI expertise.
  • Deploy training and skills development activities for researchers at all levels using the flagship datasets, spanning ethics, tools, and standards.
  • Increase the range of perspectives by encouraging broad exposure to AI-READI dataset from a variety of individuals.


  • AI-READI Internship Program

    One component of AI-READI is the Skills and Workforce Development Module, which includes the development of a yearlong mentored research internship program aimed at expanding the future workforce at the intersection of data science/AI and the biomedical sciences and clinical research.

Intern Orientation and Onboarding

Photo of the UAB Callahan Eye HospitalPhoto of the UCSD Medical CenterPhoto of the UW Medicine building

Faculty at UC San Diego hosted an immersive AI training bootcamp for a group of interns participating in the AI-READI program. Program PIs Sally Baxter, MD, and Linda Zangwill, PhD are overseeing the yearlong research internship program, and the bootcamp itself was led by UC San Diego Halıcıoğlu Data Science Institute faculty Virginia de Sa, PhD, Bradley Voytek, PhD, and Gary Cottrell, PhD.
Bootcamp participants engaged in hands-on practice in programming languages and learning fundamentals regarding AI and machine learning. The participants included a wide range of individuals ranging from master's students to postdoctoral fellows coming from a broad range of disciplines.


Meet the people behind the scenes who make it all happen.