441 computer-security-"https:"-"https:"-"https:"-"UCL" PhD positions in United Kingdom
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undertake an interdisciplinary programme combining polymer synthesis, materials characterisation, rheology and mechanical testing, and in vitro drug release studies, supported by quantitative analysis and
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. Note that this is an in-person programme, so you will need to be within regular commuting distance of your University. Eligibility and requirements We want PhD researchers who are curious and excited
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ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of
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There is growing UK and international interest in networked sensing and autonomous collaborative platforms, where multiple airborne sensors co-operate to collect and exploit data. In contrast to single-platform radar systems, distributed Synthetic Aperture Radar (SAR) architectures offer...
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importance to a binary assessment of effectiveness. As such, the aim of this PhD programme is to comprehensively evaluate football officiating decision support systems. Identify aspects of newly developed
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Group Reps to enhance the research environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access
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or computer science is desirable but not required. An interest in interdisciplinary communication and engagement as well as an understanding of how AI is currently deployed in science is welcomed but not essential.
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standard entry requirements for the Psychology PhD programme . Essential Criteria At least a high 2:1 bachelor’s degree in Psychology or a related field High 2:1 or equivalent in an undergraduate research
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apply a broad range of research methods including advanced statistical methods, computational modelling and experimental design, with the aim of generating policy-relevant evidence. The student will work
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Description: Human-wildlife conflict is widespread, yet current monitoring systems aiming at their reduction remain costly, vulnerable, and difficult to scale. This project will focus on computational and