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different hypotheses, this thesis will combine an empirical in-situ approach (field surveys and plot monitoring through on-farm experimentation) with a predictive in-silico approach (modeling and meta
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predictive models, and interpreting large environmental datasets, collaborating in interdisciplinary projects and in the production of scientific publications. In the performance of duties, it may sometimes be
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-driven methods provide excellent performance under low or cyclo-stationary regimes but struggle with highly dynamic and rapidly varying conditions; conversely, model-based state observers ensure robustness
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with experimentalists to validate predictions made by their machine-learning models and drive wet-lab discoveries. The candidate may also have opportunities to work with research software engineers
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. Combining AI-based prediction (e.g., TCNN, LSTM, etc) with musculoskeletal models to estimate and predict muscle activation and tendon force over short horizons (e.g. ~200 ms). Integrating these predictions
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. However, in many real-world and latency-critical applications, performance cannot be assessed solely through final recognition accuracy. Instead, the value of a prediction strongly depends on its timeliness
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genetics to predict breast cancer risk and tumour aggressiveness in BRCA variant carriers Digital biomarkers for enhanced AI-guided therapy in heart failure (D-BEAT) Experimental models for optimizing
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scalable IoE energy management strategy; 4) to develop agile IoE fault detection and accurate failure prediction methods; 5) to construct an intelligent energy optimisation system. SAILING combines excellent
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) to design an intelligent and scalable IoE energy management strategy; 4) to develop agile IoE fault detection and accurate failure prediction methods; 5) to construct an intelligent energy optimisation system
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Law, CRCF). It will develop AI tools to map and predict soil health across space and time, accelerate literature reviews, extract best management practices from long-term experiments, and design methods