A Multimodal and Interdisciplinary Data Science Training Program to Enhance a Diverse Workforce for Addiction Research - PROJECT SUMMARY The proposed training program aims to address the lack of specialized training in Artificial Intelligence (AI) and Machine Learning (ML) methods for addiction research in Mississippi’s major universities. The program is featured by its evidence-based multimodalities and extensive interdisciplinary collaboration across three campuses (University of Mississippi at Oxford, University of Mississippi Medical Center at Jackson, and the historically black university Jackson State University). The program emphasizes fostering a diverse data science workforce by collaborating with Jackson State University and making concerted recruitment efforts to engage underrepresented students at other participating campuses. The program encompasses five integrated components that create a progressive learning pathway while ensuring sustainability, including webinars (W), summer academies (A), symposiums (S), a research lab (R), and an e-learning platform (E) branded as WAS_RE. The novel creation of a progressive learning pathway facilitates underrepresented students' access to studying AI/ML for addiction research and their engagement throughout the learning process. The WAS_RE program begins with a series of webinars to raise campus-wide awareness and interest in applying AI/ML for addiction research. It then progresses to the recruitment of dedicated undergraduate and graduate students (n = 20 annually) and provides them with expert-led hands-on training during a four-week summer academy, including a symposium day at the end to further enrich the learning experience. The program will then further establish a dedicated research lab as a central hub for collaborative mentoring, providing mentored research experiences to motivated undergraduate and graduate students (n = 6 annually) who have participated in the summer academy or have equivalent capacities in applying AI/ML for addiction research. Furthermore, the program will create an e-learning platform to expand the program’s reach by distributing webinar recordings and to ensure sustainability through offering a self-paced course adapted from the summer academy curriculum. The successful implementation of this training program is expected to produce a well-trained, diverse workforce proficient in data science methods for addiction research, inspire students to pursue advanced degrees in this field, foster enduring collaborations across disciplines and institutions, and advance the field’s ability to tackle intricate addiction challenges.
