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Accountabilities Design and implement software pipelines to deploy ML models on edge devices with real-time inference capabilities. Optimize machine learning models (e.g., quantization, pruning) for edge hardware
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and access to your own car is essential. You will be joining a small team of 8 colleagues and 1 regular volunteer, with varying experience levels, who have worked for the charity between 1 and 9 years
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. Our team brings together deep expertise in software engineering, distributed systems, machine learning, and cybersecurity. We work across disciplines; from healthcare predictive models for urban air
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stakeholders Knowledge of new and emerging digital tools and their application within urban planning and design (for example, the growing use of AI/Machine Learning in local planning authorities) Lecturer Grade
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-grained simulations, advanced sampling, and machine learning for predicting and analysing short-lived protein conformations. Enhance and automate workflows for reproducible simulations and structure-based