Educating the workforce of tomorrow is an increasingly critical challenge for areas such as data science, machine learning, and artificial intelligence. These core skills may revolutionize progress in areas such as health care and precision medicine, autonomous systems and robotics, and neuroscience. Skills in data science and artificial intelligence are in high demand in industrial research and development, but we do not believe that traditional recruiting and training models in industry (e.g., internships, continuing education) are serving the needs of the diverse populations of students who will be required to revolutionize these fields. Our program, the Cohort-based Integrated Research Community for Undergraduate Innovation and Trailblazing (CIRCUIT), targets trailblazing, high-achieving students who face barriers in achieving their goals and becoming leaders in data science, machine learning, and artificial intelligence research. Traditional recruitment practices often miss these ambitious and talented students from nontraditional backgrounds, and these students are at a higher risk of not persisting in research careers. In the CIRCUIT program we recruit holistically, selecting students on the basis of their commitment, potential, and need. We designed a training and support model for our internship. This model consists of a compressed data science and machine learning curriculum, a series of professional development training workshops, and a team-based robotics challenge. These activities develop the skills these trailblazing students will need to contribute to the dynamic, team-based engineering teams of the future.
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