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research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research
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, and collaborative development experience with artificial intelligence or machine-learning tools and methods, particularly their application to mathematical research or software development. This may
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are particularly interested in: machine learning for molecular and omics data, including representation learning for biological sequences and structures, and the integration of multiple omics layers machine learning
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machine learning approaches relevant to breast cancer research and medical imaging, where appropriate collaborate with multidisciplinary teams including radiologists, radiographers, clinicians
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on future long autonomous navigation techniques. About you a PhD in a relevant field or near completion extensive knowledge of robotic navigation, machine learning or other relevant fields experience working
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extensive knowledge of robotic navigation, machine learning or other relevant fields experience working with marine robotic systems or the data they collect, including inertial, acoustic, visual and
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passion for applying advanced machine learning to real-world medical challenges. If you thrive in collaborative, multi-disciplinary environments and possess a strong technical foundation in AI methodologies
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interactions, and environmental stimuli, with applications in wearable technologies, intelligent sensing systems, human–machine interfaces, healthcare monitoring, and soft robotics. Key responsibilities include