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PhD: Systematic Exploration of Robot Behaviours for Manufacturing Tasks to Automatically Discover Failure Scenarios EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering
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global change, damaging critical infrastructure resilience. This project is part of the prestigious Loughborough University Vice Chancellor’s PhD Cluster – RAINDROP (Resilient eArthwork INfrastructure
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improve surgical workflow, shortens surgery time, enables unrestricted movement tracking, and reduces infection risks. Eliminating markers enables robot-assisted or fully automated femoral implantation
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the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute for Demographic Research (MPIDR), in
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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by UK utility SP Energy Networks, and is used to automate the selection, siting and sizing of network operator-owned active PEDs. An initial design for the Tool has been developed through 2025, and
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from all backgrounds to join our community. The Nonlinear Systems and Control group (https://www.aalto.fi/en/department-of-electrical-engineering-and-automation/nonlinear-systems-and-control ) at Aalto
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industries, including transportation, consumer electronics, and industrial automation. This PhD project focuses on the design and optimization of intelligent systems with an emphasis on energy efficiency and
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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This PhD opportunity at Cranfield University invites candidates to explore the integration of AI into certification and lifecycle monitoring processes for safety-critical systems. The project delves