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and apply machine learning and deep learning models to analyse complex, multi-dimensional datasets, including spatial transcriptomic, proteomic, and single-cell sequencing data. The candidate will
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project
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federated learning and multimodal deep learning models for healthcare. The project will focus on enabling privacy-preserving learning from distributed healthcare data sources, including longitudinal medical
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experience, deemed equivalent by the GRC (or delegate). The ideal PhD candidate will have: A strong background in machine learning, deep learning, and signal processing Proficiency in Python and machine
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video