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Qualification: Master in Computer Science and/or Cybersecurity or equivalent degrees with expertise in at least one of the above areas (dependability, real-time systems, operating systems) Experience in dependable systems, real-time and embedded systems and/or operating systems and the threats...
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The ARC funded project will create multifunctional fabric designs & engineering techniques integrating improved heat and flame protection, comfort and smart features into multilayered personal protective garments. Two doctoral scholarships are available for outstanding applicants to work on this...
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multilingual NLP, AI ethics, or culturally inclusive AI safety is strongly encouraged. Candidates must meet minimum PhD entry requirements, including an Honours Bachelor's degree (4 years) with a Distinction (70
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Subject areas: Conflict and security. A fully funded EPSRC studentship to fund a doctoral research project aimed at improving communication between technical & non-technical cybersecurity
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care. There is evidence that clinical debriefing models can mitigate the psychological effects of these stressful events and improve the psychological safety of their working environment to improve
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to conduct research related to social safety? As a PhD candidate, you will investigate the complexities of digital written workplace communication. You may formulate your own research, which will contribute
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the Head of Department. You will be supervised by Associate Professor Hyungju Kim. About the project This project aims to develop comprehensive safety checklists tailored for the maritime industry, with a
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Safety from wandering with enhanced privacy for people with mild dementia DoS: Hai-Van Dang, (hai-van.dang@plymouth.ac.uk ) 2nd Supervisor: Mona Nasser, (mona.nasser@plymouth.ac.uk ) Applications
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storage also presents security risks, making data more vulnerable to cyberattacks and unauthorized access. Moreover, transmitting large datasets leads to high communication costs, increased bandwidth
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PhD Studentship: Secure By Design Datasets – Distillation and Privatisation for Future Collaboration
researchers can struggle to find the data needed to train machine learning models. This project will develop an AI-driven “secure-by-design” approach to dataset privatisation and distillation, enabling