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operational data and machine learning. You will be based at UCL mechanical Engineering, and collaborate with industry and port partners on system design, prototyping, and lab-based trials. Key responsibilities
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of publications. Criteria Essential or desirable Stage(s) assessed at A PhD (or close to completion of a PhD) in Machine Learning or a similar area (e.g. in Computer Science, Electrical and Electronic Engineering
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning, epidemiology
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bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full
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UKESM1 or similar models, advanced data analysis and machine learning, would be advantageous. Grade E: You will be near completion of a relevant PhD or have equivalent research experience, and be able
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the areas: AI, deep neural networks, machine learning, applied topology, probability, statistics, signal processing. About the School The School has an exceptionally strong research presence across
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optimisation is also essential. Evidence of participation in funded R&D projects in the UK or overseas in some of the areas of: Wireless communications, MIMO, RIS, optimisation, machine learning and game
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human
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bioinformatic workflows. Familiarity with biomedical ontologies and text mining on Electronic Health Records and biomedical literature Knowledge of machine learning / deep learning with an interest in
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Supervised Machine Learning and Reinforcement Learning. The objective is to significantly enhance battery performance and longevity. While conventional methods rely on either physics-based models or high-level