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communication skills and preferably experience of using Python and machine learning in an applied context, preferably in a healthcare environment. This role is a part time (7.3 hours per week) fixed term
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to relevant research case studies within the AI4CI Research Hub. Developing data pipelines, machine learning models, and smart agents in simulated and real environments to develop and test hypotheses around the
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pipelines, machine learning models, and smart agents in simulated and real environments to develop and test hypotheses around the application of AI in developing resilience to pandemics. Analysing historical
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the department. Areas that we aim at covering include but are not limited to: AI and Machine Learning, with interest to ground, aerial, and marine robots. About you You should have a PhD in Robotics, AI, or a
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have a PhD in a relevant area as well an appropriate track-record of high quality research outputs in the field of Artificial Intelligence / Machine Learning, and clear and ambitious plans for future
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collaborative, interdisciplinary setting. You must hold (or be about to receive) a PhD in Statistics, Data Science, Computer Science, or a related discipline. Substantial experience applying machine learning
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language understanding and generation, which further enhances the potential of user simulators using language models as backbones. This PhD project is part of an ongoing collaboration with researchers from UCL and the
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will initially be focused on developing and evaluating machine learning and statistical modelling tools to predict and classify disease trajectories using large scale health records databases to answer
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recruiting Associate Lecturer (Teaching) positions to support our developing education portfolio in Robotics & AI, based in our new UCL East Campus. About the role The post-holder would be expected to teach
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to unravel the regulatory principles underlying the dynamics of intracellular signalling. We build these models by blending techniques from mathematical modelling and machine learning. More details about the