No ratings yet
Taught by or worked with Scott? Your rating helps other students choose.
Professor Scott Hazelhurst is a Professor of Bioinformatics in the School of Electrical and Information Engineering at the University of the Witwatersrand. He holds a BScHons and MSc from the University of the Witwatersrand and a PhD from the University of British Columbia. He also serves as a Senior Scientist at the Sydney Brenner Institute for Molecular Bioscience. His research focuses on bioinformatics, including tool and algorithm development, genome-wide association studies, population structure analysis, and the application of high-performance computing to molecular biology problems. He is the principal investigator of the Wits node of H3ABioNet and a collaborator on the H3Africa AWI-Gen project investigating genetic and environmental factors in cardio-metabolic disorders in African populations. He leads the MADIVA Research Hub on multimorbidity in Africa under the Data Science Innovation for Health in Africa Initiative.
Throughout his career at the University of the Witwatersrand, Professor Hazelhurst has contributed to advancing computational approaches in genomics and precision medicine relevant to African populations. He has supervised numerous postgraduate students and postdoctoral researchers in bioinformatics and related fields. In 2022, he was part of the research team that received the NRF Science Team Award. His work supports large-scale genomic studies and the development of bioinformatics capacity across the continent through collaborative networks and projects.
Discover how Wits University researchers have developed a groundbreaking model for ethical health data sharing, enabling responsible collaboration in multi-site studies across Africa.
Discover Wits University's MADIVA framework for ethical health data sharing, balancing openness with protection in African multimorbidity research. Insights into policy, impacts, and future for higher ed.
Wits University's AGenDA initiative publishes over 1000 diverse African genomes in Nature, uncovering novel variants to boost disease prediction accuracy and advance equitable precision medicine.
Photo by Precondo CA on Unsplash
Photo by Brecht Corbeel on Unsplash
Photo by Anne Nygård on Unsplash
Photo by Kelly Sikkema on Unsplash
Photo by Markus Winkler on Unsplash
Photo by Philip Strong on Unsplash
