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detection, statistical detection models and mathematical models of image processing; (iii) demonstrate experience in academy-industry projects; (iv) interest in publishing high-quality journal papers in
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multiple modalities of medical imaging (e.g. fundoscopy images, OCT scans, MRI, CT, X-ray and digital pathology). We bridge the gap between machine learning research and clinical practice through fruitful
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focuses on developing digital tumor models that integrate clinical and molecular data to predict treatment response, therapeutic resistance, disease progression, recurrence, toxicity, and survival. We work
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and adolescent sexual behaviours in contemporary digital contexts. This exciting research initiative addresses a significant and under-examined challenge at the intersection of children's rights, sexual
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/exosomes. Advanced cell culture, molecular biology and imaging approaches will be combined to study cellular responses and mechanisms relevant to oral disease and regenerative medicine. The overall aim is to
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intelligence, including machine learning and computer vision, robotics, and physics-based modelling, the DISC Lab pioneers new methods for monitoring, digitalization, and automation in construction. We
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Preferred Qualifications: Field experience with drone surveys Experience with processing drone survey data and construction of digital surface models Experience with use of Agisoft Megashape software
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extracellular vesicles/exosomes. Advanced cell culture, molecular biology and imaging approaches will be combined to study cellular responses and mechanisms relevant to oral disease and regenerative medicine
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including radiologists, radiographers, clinicians, public health researchers and health professionals medical imaging modalities such as MRI, Digital Mammography, Digital Breast Tomosynthesis, PET, CT, X-ray
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progression. Using image-based siRNA screens, we have identified novel regulators of ER-phagy. This project aims to investigate the molecular mechanisms of ER-phagy and how this contributes to cancer