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Productivity Index (RPI) using observed versus potential productivity modelled with machine learning (https://doi.org/10.1016/j.ecolind.2025.113208 ), this applied geospatial ecology project will study how
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-Intrusive Load Monitoring (NILM) can bridge this gap by turning whole-home readings into appliance-level information, with studies showing meaningful efficiency gains for households. However, deploying NILM
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for future flight. You will develop a strong expertise in computational mechanics, structural health monitoring and machine learning with a particular focus on fundamental aspects that can have far-reaching
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