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edge data processing methods for mobile MRI scanners and testing in clinical enviroment. Required knowledge Excellent programming, image processing, optimisation background Affinity to work across
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clinical decision making. Required knowledge Python programming Machine learning and deep learning fundamentals Large Language Models (LLMs) and Generative AI Multi-agent AI or AI reasoning
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learning. A publication or two in related areas will be a plus. the candidate should have strong Python/R <b>programming</b> skills. The candidate will work closely with experts in both machine learning and public health. Project funding Project based scholarship Learn more about minimum entry...
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should have a strong background in: Data Science, Artificial Intelligence and Machine Learning Python and/or R programming Data preprocessing, feature engineering and statistical analysis Supervised and
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learning. A publication or two in related areas will be a plus. the candidate should have strong Python/R <b>programming</b> skills. The candidate will work closely with experts in both machine learning and public health. Project funding Project based scholarship Learn more about minimum entry...
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should have a strong background in: Data Science, Artificial Intelligence and Machine Learning Python and/or R programming Data preprocessing, feature engineering and statistical analysis Supervised and
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Buffet, and Iadine Chades. "Interpretable Solutions for Stochastic Dynamic Programming." bioRxiv (2024): 2024-08. Wells, Lindsay, and Tomasz Bednarz. "Explainable ai and reinforcement learning—a
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diverse academic backgrounds, including computer science, data science, learning sciences, or educational technology. While prior experience with programming (e.g., Python), machine learning, or
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should also have a strong computer science background with good programming skills. Learn more about minimum entry requirements .
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, Artificial Intelligence and Machine Learning Python and/or R programming Data preprocessing, feature engineering and statistical analysis Supervised and unsupervised machine-learning techniques Deep