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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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optimization of GRAS microorganisms at 1-10 L fermentation scale. ii. Design and optimise downstream bioprocessing for protein recovery. iii. Perform characterization of protein isolates for incorporation
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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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., LLMs). Familiarity with MLOps practices like model registries and drift monitoring. High-Performance Computing (HPC): Strong command of Slurm or PBS, GPU optimization with ability to scale distributed
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from outputs based on expert knowledge in area of practice. This role demands a high level of expertise in both public and on-premises cloud environments, focusing on creating, managing, and optimizing
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Adaptive Systems, Embedded AI, Nanoelectronic AI and Task-optimized Devices and Systems. https://www.mindscdt.southampton.ac.uk About You You will work in a team and will need to be adaptable, learning
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to watch this introductory video . What will you be doing? You will play a key role in enhancing data quality and optimizing our business systems and processes. You’ll collaborate across teams
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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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, 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
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external providers. Offer professional advice focusing on optimal student outcomes based on evidence. Utilise data and feedback to measure service provision and consistency. About the School or About the