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are: Rapidly identify AMR and predict treatment responses through use of genomics and machine learning in a clinical context Detect healthcare-associated transmission of AMR in real-time and transform outbreak
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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Advisory System, or data from other implantable or wearable devices. This involves consideration of both feature-based machine learning or data science approaches and neural mass parameter estimation
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. Required knowledge Python programming Machine learning background Image analysis Video analysis Audio analysis
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Science and Artificial Intelligence, with a focus on visual reasoning and robotic systems. The Research Fellow position involves developing novel approaches that integrate computer vision, natural
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species' distributions. This project harnesses research in ecological and agent-based modelling, machine learning, and AI to increase the predictive power of models of species’ distribution shifts via “data
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The proposed PhD project aims to build a machine learning/deep learning-based decision support system that provides recommendations on precision medicine for paediatric brain cancer patients based
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their performance evaluated in terms of classification accuracy, computational speed, and overall usability. Required knowledge Deep learning (CNNs, Transformers) and computer vision Knowledge distillation for model
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, software architectures, Machine Learning
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experience with programming (e.g., Python), machine learning, or educational data is beneficial, it is not a strict requirement. The project provides ample opportunities to develop these skills over time. What