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modelling framework multiple ML tasks as mentioned above, to ease the development burden from users. It will research unified and modular modelling strategies, capable of optimally fusing and aligning diverse
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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typically international funded grants, ensuring adherence to funding regulations, and optimizing grant administration processes. The role holder will report directly to the Research Grants Manager
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from outstanding candidates with expertise in Operations Research, Management Science and Business Analytics with a focus on fundamental research in combinatorial and stochastic optimization for business
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, stochastic optimization, modern machine learning methods, scalable algorithms for advanced Machine Learning techniques and explainable AI.In teaching, the position will contribute, inter alia
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peptides on cognitive functions, functional joint health, osteoporosis, and their optimal dosage. You will work at the exciting interface between clinical data collection and sports and nutritional research
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assessments of need and identify optimal solutions. Further particulars are included in the job description. The post is full time 35 hours per week, 1 FTE and permanent In line with LSHTM’s hybrid working
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Researcher to join an interdisciplinary team working on a theoretically informed, participatory, implementation study (OPTIM-I), aiming to optimise the use of professionally trained interpreters (PTI) in
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assessments of need and identify optimal solutions. Further particulars are included in the job description. The post is full time 35 hours per week, 1 FTE and permanent In line with LSHTM’s hybrid working
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, scalability, and adaptability to various applications such as autonomous systems, IoT devices, and wearable technologies. Research Focus Areas: 1- Neuromorphic and AI-Optimized Processors: Design AI-specific