41 software-engineering-model-driven-engineering-phd-position PhD positions at Cranfield University in United Kingdom
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Models (LLMs). Orchestrating AI/ML pipelines in 6G. Developing certification and checking processes for code inside ORAN 6G. The research will be a combination of software engineering, radio
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-engine aerodynamics. The project is aligned with the acknowledged skills development needs in the areas of aircraft/propulsion integration, aerodynamics, modelling, software development, research testing
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-class facilities, enhancing their skills in materials characterisation, computational modelling, and experimental testing. These experiences will position the graduate as an innovator, ready to
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that values equity, diversity, and inclusion, gaining unique expertise in aerospace systems design and integration (airframe, engine, subsystems), system of systems optimization, multi-fidelity models
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solutions where improved knowledge of the aero-engine characteristics will be a key consideration. The overall aim of this PhD is to explore novel measurement methods that can improve the assessment of aero
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There is an urgent need for novel freshwater quality monitoring solutions to help mitigate the risks that contaminants pose to water security, human wellbeing, and biodiversity. This funded PhD
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, multidisciplinary PhD research projects across areas such as: Zero Emission Technologies. Ultra Efficient Aircraft, Propulsion, Aerodynamics, Structures and Systems. Aerospace Materials, Manufacturing, and Life Cycle
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Join our exciting PhD programme in Security Automation and be at the forefront of changing the way we protect ourselves from cyber threats. In today's ever-evolving digital world, we urgently need
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engineering, digital technologies, and systems thinking. The university’s strong reputation for applied research and its focus on technological innovation ensure that this project will be well-supported, with
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical