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. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine learning models without moving sensitive or large
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deliveries). You will build a prototype algorithm that can be used by infrastructure and civil engineering professionals to better evaluate cable and pipeline location data. Your tasks will include: 1
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-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning algorithms that maximize the information extracted from
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algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement learning. Deep
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control algorithms lies a physics-based simulation model, whose accuracy largely determines the effectiveness of the control loop. Position 3 – High-fidelity simulation of the LAFP process Current
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MSc courses in Civil Engineering, and operates across the three main themes of Construction, Transport and Water. The Department has around 50 academics distributed over nine Chairs. About the
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. Sustainable and energy-aware orchestration of softwarized network functions. Dynamic resource allocation and optimization across distributed cloud–edge infrastructures. Performance analysis in simulators and
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terms of technologies, infrastructures, (geo)spatial distribution, scale and related investment needs matters for how and which stakeholders are affected, who gains or loses power, and how benefits and