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Field
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models to enhance learning through AI technology. A part of this work is also to consider opportunities for innovation related to start-up companies. The approach followed encapsulates Design-Based
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models to enhance learning through AI technology. The PhD fellow will engage with developing and evaluating models and agents, as well as, multi-agent networks that support the human learning and improving
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King's College London Department of Engineering | London, England | United Kingdom | about 13 hours ago
science interlink prevention and prediction of wildfire risk, by contributing to the development of a fundamental physical model to understand the process of fire spread for wildfires, as part of a European
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design of experiments strategy, a probabilistic (e.g. Gaussian Process Regression) model to describe the relationship between process parameters and material properties will be developed and subsequently
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to do a PhD and why you are suitable for this position. CV (max 2 pages) A certified copy of your master's degree and your course grades. Copies (or drafts) of your master's thesis and other documents
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you are suitable for this position. CV (max 2 pages) A certified copy of your master's degree and your course grades. Copies (or drafts) of your master's thesis and other documents, such as publications
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noise models, with particular relevance to the practical constraints of the NISQ era. This position offers not only the opportunity to pursue and shape an independent research agenda but also the
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, dynamic simulation, additive/classical fabrication; sensorization, actuation, and integration on gantry/field robots. For PhD#3 (DT): Design software architecture; integrate multi-modal data and models (e.g
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, the project aims to collect and analyse bilingual infant-directed speech, test infants’ reliance on sound cues, and use computational models to simulate the learning of two languages from speech. Your job In
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of Electrical Engineering. Project description: Autonomous vehicles for mining and mobile robotics for industrial processes require complex motion planning as well as safe model-based predictive control and