Grant Abstract: Increasing and Diversifying Future AI-Precision Nutrition Research Workforce to Promote Nutrition Health Equity among Underserved Populations
Grant Number: 1T32MD018933-01
PI Name: Kim
Project Title: Increasing and Diversifying Future AI-Precision Nutrition Research Workforce to Promote Nutrition Health Equity among Underserved Populations
Abstract: Currently, there is a critical shortage and lack of diversity of individuals, particularly underrepresented groups trained at the interface of computational approaches or integrated data science skills and precision nutrition to analyze and interpret large and complex databases of individual characteristics to resolve nutrition health disparities. This application, aligning with the NIH AI-Precision Nutrition (AIPrN) program goal, proposes a new predoctoral and postdoctoral AIPrN research training program at Prairie View A&M University (PVAMU), a historically black university (HBCU), designed to provide multidisciplinary training in computational data skills and precision nutrition to address the nutrition health disparities based on simulations and real-world research projects covering obesity, type 2 diabetes, cardiovascular diseases, and cancer among underserved populations. The aims of this proposal are to 1) recruit, train, and financially support underrepresented predoctoral students and post-doctoral fellows in AI/ML or nutritional science to the AI-Precision Nutrition research training program as a mechanism to increase the number of effective and diverse scientists integrating AI and Precision Nutrition to address nutrition health disparities; 2) develop and enhance research training program, technical assistance, and mentorship opportunities for such trainees to prepare, build capacity, and advance the field of knowledge and collaborative and integrated research in AI-Precision Nutrition approaches to tackle nutrition health disparities; and 3) provide professional development and foster leadership skills in AI-Precision Nutrition for our trainees who are positioned to apply for fellowships, grants, and as a way to facilitate exposure to careers in AI- Precision Nutrition research and transition to research-intensive careers in academia, industry, the NIH, and private foundations. These objectives will be met through rigorous didactic training, mentorship, engagement in laboratory rotations for sample research projects, and professional and career development with a team of 12 faculty mentors that span across the chronic diseases mentioned in inclusive and diversity-friendly institutional research environments at PVAMU and the USDA/ARS Children Nutrition Research Center, Baylor College of Medicine (CNRC). Three predoctoral students and 1 postdoctoral fellow will be recruited each year over the 5- year grant cycle from the highly underrepresented pool of applicants to PVAMU. During the course of their research training, predoctoral students and postdoctoral fellows will attend professional development workshops and seminars in grant writing, manuscript development, career development advising with the Career Services, and the NIH mandatory annual cross-site BSSR Data Analytics T32 Program grantee meetings. PVAMU, an HBCU with relevant programs in AI/machine learning and precision, and the cutting-edge research at CNRC, positions the two institutions to propel the goal to increase and diversify qualified scientists and practitioners in this field to address nutrition health disparities. PUBLIC HEALTH RELEVANCE: (3 sentences) Prairie View A&M University (PVAMU) will partner with the Children’s Nutritional Research Center at the Baylor College of Medicine to create a T32 training program to train Ph.D. students and post- doctoral fellows to study precision nutrition research with AI and machine learning skills. The training program at PVAMU, an Historically Black College and University (HBCU), can significantly improve the diversity in the future workforce in precision nutritional research.
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