AU25 Bachelor of Biomedical Science - Bachelor of Mathematics Queensland University of Technology
Understanding data - how to analyse it, model it and make useful predictions from it - will continue to underpin new technologies, processes and discoveries in all areas of the economy.
In the case of biomedicine, the increased capacity to generate large datasets from patients and or treatment regimens requires graduates with a capacity to understand both the biology and the mathematics.
In the Bachelor of Biomedical Science you'll study how the body works, investigate how disease or injury interferes with normal function, and treatment strategies that help restore function. You will also have a high degree of course flexibility with the option to select one major or two minor areas of study that align with your interests.
In the Bachelor of Mathematics you'll learn to be an agile problem solver, capable of tackling real-world problems in their full complexity, through the application of modern mathematical, statistical and computational approaches. Your specialist knowledge and skills in one of the contemporary specialisations of mathematical practice - applied and computational mathematics, statistics, and operations research - will be underpinned by a solid foundational base of mathematical training, and complemented by computational and programming skills.
With increased demands upon the health system, a digital transformation is underway to provide better quality and efficiency of care, better population health and a better overall patient experience.
There is tremendous opportunity and demand for graduates with the skills to connect mathematical, statistical and computational knowledge to applications in the health and biomedical sciences, such as omics, bioinformatics, clinical decision making, device and technology manufacture, and patient care and optimal scheduling.
With electronic health records being rolled out in hospitals across Queensland, there is also a need for graduates who are skilled in mathematical modelling and simulation, analysis and interpretation of data, and scheduling and optimisation, to promote evidence-based decision-making for health practitioners.
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