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Field
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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benefit society by advancing technologies that will underpin the design of the next generation of transport aircraft. Specifically, you will develop, test, and industrialise algorithms designed to simulate
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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on AI-driven end-to-end autonomous driving algorithms. Key Responsibilities: The research fellow will be leading the development of AI-driven end-to-end autonomous driving algorithms. The work will
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connections to projects in which the CCA is involved (if relevant) Expertise in technical elements of computational astrophysics research, which may include but are not limited to: algorithm and software
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Wearables & Healthcare Systems Theme 3 Algorithms for Privacy, Security and Provenance Theme 4 Clinical Innovation & Translation Connected medical devices are increasingly employed in the drive towards
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Wearables & Healthcare Systems Theme 3 Algorithms for Privacy, Security and Provenance Theme 4 Clinical Innovation & Translation Connected medical devices are increasingly employed in the drive towards
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Responsibilities: The successful applicant will be responsible for: Obtaining theoretical results at the interface of geometry and biophysics Designing, implementing, and testing algorithms to model active matter
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benefit society by advancing technologies that will underpin the design of the next generation of transport aircraft. Specifically, you will develop, test, and industrialise algorithms designed to simulate
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automation in food manufacturing - smart sensors, digital twins, and AI-driven food quality control and processing; Food safety - supply chain tracking/monitoring, blockchain Biotechnology: Host strain