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Deadline for R25 Fellow Applications

March 14

Announcement Release Date: January 18, 2022
Application Receipt Date: March 14, 2022 by 5 p.m.
Notification of Outcome: All applicants will receive notification by April 30, 2022
Earliest Project Start Date: May 16, 2022

Background: Supported by NIAID (R25AI164581-01), the UofSC Big Data Health Science Center (BDHSC) has been implementing a Big Data Health Science Fellow (“Big Data Fellow”) program since 2021. The multiple, massive, and rich Big Data streams in healthcare (e.g., electronic health records, mobile technologies, wearable devices, genomic data) and the emergence of advanced information and computational technologies (e.g., machine learning and artificial intelligence) offer an invaluable opportunity for applying innovative Big Data science research in NIAID focus areas of infectious diseases such as HIV/AIDS and COVID-19. Big Data science has the potential to identify high-risk individuals and communities and prioritize them for early biomedical or public health interventions, predict long-term clinical outcomes and disease progression, and evaluate public health policy impact. Key to addressing these complexities is a critical mass of health researchers with adequate knowledge, competencies, and skills to unlock important answers from Big Data to better understand, treat, and ultimately prevent these diseases and related comorbidities. However, there is a nationwide shortage of talent with such knowledge, competencies, and skills, especially in traditional academic settings. While junior faculty, as part of the generations of digital learners, have the greatest potential to develop their Big Data health science research agenda, many face multiple structural barriers to conducting Big Data science research. Such barriers include the lack of protected time to initiate new interdisciplinary Big Data research, opportunity to participate in funded Big Data research, and adequate mentoring. The Big Data Fellow program, as part of the BDHSC’s professional development mission, is designed to address these gaps and promote Big Data health science research at UofSC.

Program Goals and Aims: The program will recruit about 4 UofSC health science junior faculty per year and provide them with salary support (25%) to participate in the training program with the following specific aims:

Aim 1: Provide courses for competency and skills development in BDS research. Each trainee will complete 2 formal or informal courses (one per semester) in BDS areas that are appropriate for their background and research interests.
Aim 2: Engage trainees in hands-on research and proposal development. Trainees will participate in ongoing NIH-funded Big Data research projects that utilize existing large data sources (e.g., NIH COVID-19 Cohort Collaborative [N3C] Data, SC statewide HIV and COVID-19 data and VA system-wide HIV and COVID-19 data). 
Aim 3: Provide trainees with rich mentoring experience in BDS research and professional development. Each trainee will be mentored by a team of NIAID-funded investigators who have complementary knowledge and skills from multiple domains (clinical medicine, public health, biostatistics, computing, geospatial science, social media, etc.,) and will engage in contextual mentoring and peer-to-peer mentoring.

Program Benefits and Support:
The program will provide the following support to Fellow during the training year:

  • 25% salary support for one year (subject to NIH salary cap)
  • Support for participation in grant writing bootcamp
  • Matched with a mentoring team
  • Participation in a funded Big Data research project
  • Support in NIH grant preparation and submission

For questions related to various aspects of the Big Data Fellow program, please contact any of the following individuals:

Xiaoming Li, Ph.D., xiaoming@maillbox.sc.edu

Jiajia Zhang, Ph.D., jzhang@mailbox.sc.edu

Miranda Nixon, MA, mc95@mailbox.sc.edu

Full RFA Available Here


March 14