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in our mission to develop clinically useful algorithms, drive high-impact publications, and pave the way for personalised breast cancer treatments. Analyse data from cutting-edge technologies
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AI solutions? We are launching a pioneering research and innovation hub in AI-one that will shape the way humans and machines collaborate for decades to come. Led by Prof. Usama Fayyad, the Institute
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generation data-driven stochastic and distributionally robust optimization methodologies or (ii) develop advanced fairness promoting stochastic optimization frameworks. In coordination with Prof. Shehadeh
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techniques for integrating such solutions into modern SDV middleware. Responsibilities: Conduct research in runtime analysis and reconfiguration of in-vehicle TSN networks. Develop algorithms and prototypes
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. The overall aim of this project is to address these challenges by: Developing new data-driven and physics-based models of battery behaviour. Designing advanced BMS algorithms for real-time monitoring and
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward
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the developmental rules underlying phenotypic variation. The successful postdoctoral fellow will develop and implement an empirical framework that utilizes data-driven algorithms to learn relationships between past
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entails the development of heuristic and metaheuristic algorithms, as well as GIS map integration, for the most effective management and suppression of wildfires. You will work in an international team
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research in neuro-symbolic AI, with a focus on using generative AI and prompt engineering as a method to engineer knowledge graphs one can trust. This includes the design of algorithms and architectures, but
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Prof Lyudmila Mihaylova Application Deadline: Applications accepted all year round Details This research project focuses on the development of methods for intelligent wildfire detection and localisation