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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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Computer Science, Electrical & Electronic Engineering, or equivalent. Background knowledge in signal representation/processing, data-driven and machine learning/analysis, esp in climate related topics. Prior
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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, or other related fields. Solid Mathematical skills. Experience in implementing algorithms for machine learning and natural language processing-related applications (It would be good if the candidate can also
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methods Experience analysing RNAseq and/or high throughput imaging data Experience handling human post-mortem tissue Experience writing/using computer code Experience supervising postgraduate students and
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engineering, membrane mechanics, biomolecular assembly and related techniques, mechanical modeling and simulation is highly preferred. Experience in advanced microscopy, super-resolution cell imaging, machine
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cell imaging, machine learning-based image analysis is highly preferred. Have more than 2 first-authored papers in reputable journals is preferred. We regret that only shortlisted candidates will be
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to validate theoretical approaches, utilizing machine learning techniques to derive meaningful conclusions. Collaborative Projects: Engage in collaborative research with interdisciplinary teams, contributing
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machine learning for real-world applications. Scalable Digital Health Solutions: Develop methodologies for reliable, long-term motion monitoring across diverse user groups and environments
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) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena