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including data engineers, clinicians, software developers, and lived experience experts to: Scope and integrate new datasets into an new web interface, focusing on mental health-relevant omics and real-world
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
opportunities. As part of Cranfield University’s strong industry and research network, the student will have the chance to attend international conferences and present findings at key events in the fields
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interest in expanding their knowledge in both domains. (1) Geometry/Topology -related methods in computer science. (2) Machine Learning. (For example, graph neural networks, generative networks, or neural
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of the Hub. Our approach enhances T2 (Interconnected QC systems) through verification methods for connected networks, supports T1 (Integrated quantum demonstrators) via hardware-agnostic metrics, and enables
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innovation through applied research, bridging academia and industry. Students will have access to state-of-the-art laboratories, hardware/software resources, and design facilities, supporting AI-powered
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applied research, bridging academia and industry. Students will have access to state-of-the-art laboratories, hardware/software resources, and design facilities, supporting AI-powered electronics research
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, Cranfield fosters innovation through applied research, bridging academia and industry. Students will have access to state-of-the-art laboratories, hardware/software resources, and design facilities
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, including excellent pension schemes, flexible working, generous holiday entitlement and more . Our Northumbria Values, co-created by our team, define who we are: Academic Excellence, Innovation, Inclusivity
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position (2 + 2 model) under the supervision of Sebastian Szyller. Trustworthy & Adversarial Computing Lab is a newly established group. The lab has an extensive network consisting of companies and academic
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to learn the following skills: 1. Ultrasound imaging 2. Transcranial doppler 3. Recording and analyzing physiological data including intracranial pressure using power lab, Moberg, ICM+, or similar software