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project - “UAV-based inspection of aircraft with deep learning-based visual inspection system”. Qualifications Applicants should have a higher diploma or a diploma or an equivalent qualification in
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Professor Arbel’s lab in the context of a grant focused on developing multi-modal causal deep learning models to predict future disability progression and treatment response in Multiple Sclerosis
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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project - “Deep learning-based approach for process parameter optimization of SiC wafer under limited data”. He/She will carry out research in the areas of machine learning and data science, and also be
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science. They should have a track record of or potential for research excellence. They should be enthusiastic about software development and have working knowledge of python and relevant deep-learning libraries (e.g
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cohorts, geometric deep learning, computational anatomy, cardiovascular modelling, multimodal datasets. What you’ll need Applicants should have a PhD (or nearing completion) in computational imaging and
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deep learning and generative AI approaches, creating synthetic virtual patient cohorts from multimodal datasets. Your work will involve designing advanced algorithms and high-throughput workflows
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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(or comparable deep learning models) for image analysis. Demonstrated expertise in digital pathology concepts, including image processing, feature extraction from whole slide images, and working with large-scale
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and