MSc Cancer Genomics and Data Science in London United Kingdom | Queen Mary University of London

The field of biomedical science has become heavily reliant on data, demanding advanced methods in cancer genomics and data analytics to process complex, large-scale cancer datasets and extract valuable insights. Yet there's a critical gap in professionals equipped with both the necessary skills and practical experience in biomedical and cancer data analysis.Enroll in a program crafted and taught by leading genomics and data science specialists who create and utilize computational methods to address research challengesAcquire practical skills by working with authentic patient and experimental datasetsMaster current analytical approaches and bioinformatics/computational tools used in biomedical and cancer investigationsUndertake a significant independent research project to enhance your analytical capabilities and research expertiseCurriculum OverviewModern biomedical science is fundamentally data-centric, with advanced bioanalytical methods generating unprecedented volumes of information about DNA, RNA, proteins, metabolites and their interactions at both tissue and single-cell levels. Cutting-edge approaches in cancer genomics and data science—including modeling, data integration, machine learning and AI—are essential for interpreting multi-dimensional cancer datasets and producing actionable findings.Yet the field faces a significant shortage of skilled bioinformaticians, computational biologists and data analysts with relevant expertise in real-world biomedical and cancer data applications. This program bridges the divide between research/industry needs and student education, providing contemporary coursework focused on "big-data" analysis supported by high-performance computing, alongside innovative research projects and hands-on training using actual cohort data.Your instructors include active researchers who develop bioinformatics and computational tools while applying them to cancer and medical research areas like genomics, proteomics, evolutionary studies, modeling and biomarker identification. Our extensive UK network of academic and industry partners contributes to teaching, jointly supervises research projects, and offers career opportunities.