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Field
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
artificial intelligence, machine learning, data analysis, or digital systems would be advantageous but is not essential. We value curiosity, problem-solving ability, and a proactive attitude toward learning
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, Data Science, or a closely related discipline Strong interest in interdisciplinary research at the interface of Artificial Intelligence, Data Science, and Life Sciences Excellent programming skills
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Everyone is talking about artificial intelligence. But who is developing the necessary chips? We are, for example! Would you like to help drive the development of a new highly efficient AI hardware
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge of interdisciplinary
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candidate to undertake research in the area of cognitive networking for 5G/6G networks, with a focus area on connected and autonomous mobility. This research will explore how artificial intelligence can be
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Project details Globally, we are facing a huge explosion in data creation volume. With technological advancements like IoT and Artificial Intelligence, organisations are gathering vast swathes
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new industries (virtual reality, platforms and artificial intelligence). Centre for Family Entrepreneurship and Ownership (CeFEO) Family ownership and family business, heterogeneity in family ownership
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universities and industry leaders, the Hub aims to advance manufacturing productivity, resilience, and global competitiveness through innovative digital solutions powered by Digital Twins, Artificial
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Language Model, or Artificial Intelligence be used? The impact of this research will be to enable practitioners and the stakeholders of systems models to make objective assessment of model qualities using