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Computational Methods for Advanced Research to Transform Biomedicine (SMARTbiomed ), an international collaboration that integrates large-scale, multimodal biomedical data with advances in statistical and machine
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Computational Methods for Advanced Research to Transform Biomedicine ( SMARTbiomed ), an international collaboration that integrates large-scale, multimodal biomedical data with advances in statistical and
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fundamental algorithms for producing policies for rich goal structures in MDPs (e.g. risk, temporal logic, or probabilistic objectives), and modelling robot decision problems using MDPs (e.g. human-robot
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The Role The successful applicant will be responsible for the design, development, and implementation of deep learning and computer vision frameworks across a range of research projects
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developed goal-sequence generalization task. The project will integrate high-density silicon probe recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms
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collaboration with the Translational Gastroenterology Unit (TGU) and the Ludwig Institute of Cancer Research (LICR) we aim to develop a computer guided endoscopy image recognition system that will support
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collaboration with the Translational Gastroenterology Unit (TGU) and the Ludwig Institute of Cancer Research (LICR) we aim to develop a computer guided endoscopy image recognition system that will support
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type (iv) work with the computational biology team to transfer this information into a AI algorithm that can distinguish neurodegenerative and neuroprotective phenotypes (v) work with colleagues in
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches