The Supervised Research Training Program (SRTP) offers participants the opportunity to deepen their expertise through four carefully curated specialized tracks. Each track is designed to provide domain-specific knowledge, practical skills, and mentored research experience, empowering trainees to address pressing challenges at the intersection of science, health, and technology.
Track 1: Bioinformatics
Delve into the world of biological data analysis. This track focuses on the application of computational methods to understand complex biological systems, including genomics, transcriptomics, and systems biology. Participants will gain hands-on experience with tools and pipelines used in high-throughput data processing and interpretation.
Track 2: Global Health
Explore the broader determinants of health and disease on a global scale. This track emphasizes epidemiology, public health policy, health equity, and the socio-economic factors influencing health outcomes. Trainees will engage with real-world data and interdisciplinary approaches to tackle international health challenges.
Track 3: Geospatial Health
Learn how location and environment influence health patterns. This track introduces spatial analysis and geographic information systems (GIS) to study disease distribution, healthcare access, and environmental exposures. Participants will use mapping tools and spatial statistics to visualize and interpret health data in context.
Track 4: AI for Health
Harness the power of artificial intelligence in advancing healthcare. This track covers machine learning, data mining, and predictive modeling applied to biomedical and clinical data. Participants will work on projects involving diagnostic algorithms, health informatics, and ethical considerations in AI deployment.
Track 1: Bioinformatics
Delve into the world of biological data analysis. This track focuses on the application of computational methods to understand complex biological systems, including genomics, transcriptomics, and systems biology. Participants will gain hands-on experience with tools and pipelines used in high-throughput data processing and interpretation.
Track 2: Global Health
Explore the broader determinants of health and disease on a global scale. This track emphasizes epidemiology, public health policy, health equity, and the socio-economic factors influencing health outcomes. Trainees will engage with real-world data and interdisciplinary approaches to tackle international health challenges.
Track 3: Geospatial Health
Learn how location and environment influence health patterns. This track introduces spatial analysis and geographic information systems (GIS) to study disease distribution, healthcare access, and environmental exposures. Participants will use mapping tools and spatial statistics to visualize and interpret health data in context.
Track 4: AI for Health
Harness the power of artificial intelligence in advancing healthcare. This track covers machine learning, data mining, and predictive modeling applied to biomedical and clinical data. Participants will work on projects involving diagnostic algorithms, health informatics, and ethical considerations in AI deployment.