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Field
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imaging and longitudinal data. A range of machine-learning and deep-learning techniques will be developed and evaluated for cardiovascular disease prediction and risk assessment. Advanced AI and Decision
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imaging and longitudinal data. A range of machine-learning and deep-learning techniques will be developed and evaluated for cardiovascular disease prediction and risk assessment. Advanced AI and Decision
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Primary supervisor Lan Du Research area Machine Learning Project Background and Motivation The "inverse design" of molecules from analytical spectra (such as MS2, NMR, or IR) is a fundamental
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Primary supervisor Lan Du Research area Machine Learning Project Background and Motivation The "inverse design" of molecules from analytical spectra (such as MS2, NMR, or IR) is a fundamental
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use of near-time data from healthcare providers to update these models over time. Required knowledge the candidate should have gained knowledge of statistics, statistical machine learning and deep
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use of near-time data from healthcare providers to update these models over time. Required knowledge the candidate should have gained knowledge of statistics, statistical machine learning and deep
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modalities (biological, clinical/pathological data and medical imaging), with an emphasis on developing interpretable and biologically meaningful models . Methods include machine/deep learning, image
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 21 hours ago
machine learning, deep learning and computer vision (3) Experience in CCUS modeling with numerical reservoir simulators such as CMG, Eclipse, MRST or TOUGH-React (4) Experience in inverse modeling
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, preferably including Python and modern machine learning tools. Basic knowledge of deep learning, signal processing, speech/audio processing, or statistical machine learning. Interest in working