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to improve the use of artificial intelligence. This involves continuously optimizing the basic hardware components and refining the methods used to develop them. The design flow of these circuits and (sub
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, memory, and energy requirements. The successful candidate will explore novel algorithms and model-design strategies that allow AI systems to operate effectively on edge devices, clinical environments
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-Class Environment: Access to a leading research environment specializing in hardware/software for medical wearables, translational endocrinology, and machine learning for medical time-series. Cutting-Edge
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Security, Trustworthy AI for Secure Future Open Networks, Secure and Trustworthy Hardware or AI-assisted Physical Layer Security Additional enhanced training: Leadership (CMI Level 7), Innovation, Public
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, Germany. We Offer You: A World-Class Environment: Access to a leading research environment specializing in hardware/software for medical wearables, translational endocrinology, and machine learning
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) bursaries available. Research Themes: Focus on one of our 4 key themes: Space/Terrestrial Comms and Security, Trustworthy AI for Secure Future Open Networks, Secure and Trustworthy Hardware or AI-assisted
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impairments arising from practical limitations in CV-QKD systems (e.g., bandwidth constraints, ADC resolution, phase noise etc). Emphasis will be placed on energy-efficient, low-complexity hardware solutions
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
resources. To fill this gap, this proposal aims to design novel distributed and lightweight LLMs for spectrum management in aerial 6G networks. Specifically, the project will design wireless-aware data
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. The system will serve as a platform for exploring autonomous, in-situ construction processes for future lunar applications. This involves designing and integrating the extrusion hardware, thermal
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, reducing emissions, maintaining smart grid voltage stability indicators and designing fault tolerant control strategies. Recent advances in reinforcement learning (RL) show promise for real-time energy