Abstract Today, a critical mass of previously collected linked health care data is now available for optimizing patient health outcomes. Information, insights, and intelligence existing in such health care data can be unlocked efficiently using Big Data Science (BDS).As people age and live longer, increased demand for care will be two-fold, one for those living with more comorbidities, and second the emergent risks from new infectious diseases like COVID-19.The recent NIAID strategic plan for COVID-19 highlights the urgent and important need for high-quality scientific research to improve knowledge around disease transmission, surveillance, and its impact on health outcomes, and to develop both biomedical and public health measures to mitigate illness and death. The existence of several massive, and information rich big data streams in healthcare (e.g., electronic health records [EHR], mobile technologies, wearable devices, genomic data, geospatial data etc.) and the advances in information and computational technologies (e.g., machine learning and artificial intelligence) now offer an excellent hands-on training opportunity for applying innovative Big Data science (BDS) research to infectious diseases such as HIV/AIDS and COVID-19. To cultivate a thriving and talented pipeline of next generation scientists, it is essential to engage current students early and provide new and innovative training opportunities to generate interest in the biomedical, social, and behavioral, and clinical sciences. Therefore, we propose offering a 10-week Short-Term Summer Research Training Program titled “Big Data Health Science Scholar Program for Infectious Diseases” targeted towards predoctoral students in physical and/or quantitative sciences (departments of biomedical engineering, integrated information technology, chemistry/biochemistry, mathematics, statistics etc.) from across South Carolina (SC) and the United States (US). Predoctoral students completing this training will engage in experiential learning through hands- on research in infectious disease areas like HIV/AIDS, and COVID-19, both relevant to the NIAID mission. Selected predoctoral students will be paired with Program Faculty mentors from a pool of distinguished participating faculty for one-on-one mentoring. Trainees will be chosen through a competitive process based on their proposed research plan and goals for the summer experience. Specifically, we plan to recruit 8 predoctoral students from physical and quantitative sciences across the US per year (a total of 40 over the entire funding period) to participate in the 10-week summer intensive training program with the following objectives: Objective 1: Create a summer big data science training pipeline for qualified predoctoral students by exposing them to relevant courses/training for competency development in the application of BDS to infectious disease research. Objective 2: Engage trainees in hands-on research using HIV and COVID-19 data. O...