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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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flow visualisation and measurement techniques to study droplet impact under icing conditions to improve icing codes that aid in design and development of ice detection and mitigation system
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analytical frameworks grounded in Mean Field Game (MFG) theory and Multi-Agent Reinforcement Learning (MARL), which are tailored for eCPS. These frameworks will facilitate the creation of effective control
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engineering or a relevant area. An MSc degree and/or experience and good knowledge in gas turbine theory, thermodynamics, Machine Learning, and computer programming will be an advantage. Funding Sponsored by
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, computer vision or flow measurement background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience of computer coding in some form or any discipline is also
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estimation of useful life. In this research, a theory will be postulated for the combined mode of gear failures. The theory will be supported by the basic gear failure mathematics and preliminary validation