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for next-generation intelligent audio IoT sensors. Your Role and Goals As a Doctoral Researcher, you will: Design energy-efficient digital in-memory computing circuits for on-chip AI inference, spanning both
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Entanglement distribution is a foundational capability for quantum networks, enabling diverse quantum technologies including—but not limited to—quantum key distribution (QKD). QKD provides
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networks of nodes and parameters. This practice-based PhD investigates how AI can assist at the level of tool production by drafting procedural networks that the experienced technical artist can inspect
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shaping the epigenetic landscape on chromatin. Mutations and dysregulation in transcriptional regulators are a hallmark of cancer, where rewiring of enhancer networks impacts cancer proliferation
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global data such as commodity prices and weather predictions. Technological progress has made it possible to automatically collect a variety of sensor data and self-reported practice. The challenge is to
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nuclear facilities make wireless communications difficult. Expected Outcomes The PhD aims to deliver: Novel technologies enabling safe human-robot collaboration New safety and assurance methodologies
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-frequency eddy current sensor validated against real ROT measurements; (3) a real-time physics-constrained state estimator integrating JMAK transformation kinetics with the EM forward model; and (4) a model
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variations and sensors malfunctions. • Robust and efficient CF control with Level 5 EV automation tracking accuracy under harsh operating conditions, and automated identification algorithms for self
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Imperial College London is recruiting two Doctoral Candidates (DCs) to work in the Marie Skłodowska-Curie Actions (MSCA) Doctoral Network (DN) "SPARK" (HORIZON-MSCA-2025-DN-01-01), devoted to spatiotemporal
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in eddy current sensor responses. This will involve both experimental work and analytical interpretation, linking EM signals directly to underlying physical mechanisms. Key research themes include