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and execution against government grant fund objectives. Develop and validate the business model, value proposition, market-entry strategy and customer requirements. Build OEM, distributor, clinical
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, recurrent memory, Bayesian modelling, uncertainty quantification and machine learning systems. Emphasis will be on methods that design and implement new architectures for (auto-regressive) sequence modelling
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The School of Civil and Environmental Engineering (CEE) advances education, research and innovation across civil engineering, environmental engineering and maritime studies. The key objective is to
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School of Civil and Environmental Engineering is a school under College of Engineering and is a leading school for Sustainable Built Environment. The key objective of this position is to support the
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(PINNs) and surrogate modelling Time-series modelling and anomaly detection Bayesian methods and uncertainty quantification Graph Neural Networks (GNNs) Spatiotemporal data engineering Digital twins and
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anomaly detection Bayesian methods and uncertainty quantification Graph Neural Networks (GNNs) Spatiotemporal data engineering Digital twins and simulation Demonstrated Applied AI for Healthcare and
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sensors, and other sensing technologies. Develop object detection, segmentation, tracking, and pose estimation algorithms. Develop navigation, localisation, path planning, and collision avoidance algorithms
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settings. Develop and test algorithms for object detection, tracking, and classification using wireless sensors. Help guide and mentor graduate students and other junior team members working on the project
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* Design, implement, and evaluate wireless-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using wireless sensors. Help guide
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, especially where this integrates insight from sustainability. The successful candidates will report to the Head of Department and act as the leader of their research group, setting clear task objectives