Suitable training for this program would be a degree in biomedical science or biomedical engineering, ideally combined with some relevant research experience. Biomedical science graduates will be prepared to carry out computer-intensive analysis of image datasets. Engineers would be expected to have some programming (Matlab) and/or image analysis background and be open to learning biological imaging and related biological techniques. Background and/or experience with statistics would be an advantage.
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This project will address the current lack of understanding of how oocytes and resulting embryos respond to innovative oocyte maturation treatments. Using imaging-based non-invasive diagnostics combined with a big data approach, we will assess oocyte and embryo hyperspectral and morphological characteristics. High content image analysis will be combined with traditional biochemical characterisation to accurately evaluate developmental competence, inform decision-making, and optimise the likelihood of successful fertility treatment. Results from animal models obtained in this work will be validated in a clinical trial in the Fertility and Research Centre at the Royal Womens’ Hospital in Randwick.
Women's & Children's Health