54 computer-security "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "Dr" research jobs at University of Birmingham
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future of formulated polymers. We are seeking a Research Fellow in Computational Chemistry and AI/Machine Learning to advance the state of the art in understanding the degradation and biodegradation
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of Birmingham and the UK Health Security Agency. You will primarily be working in Theme 2: Applying Novel Omics Methods to Public Health Microbiology, which aims to demonstrate potential utility of new sequencing
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gives students the skills and knowledge they need to secure careers in a global marketplace. There are currently about 2,000 staff, among which about 1,000 academic staff, with an almost even split
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laboratory space, including a 200 m2 set of clean room facilities, and we maintain a Tier 2 site as part of the UK contribution to LHC world-wide distributed computing. The School of Physics and Astronomy is
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and how to present the bid to maximise the likelihood of securing the funding. Scope of the role: • Work closely with the ReLiB scientists to measure their life cycle inventories, provide LCA
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collaborators with material, and develop an understanding of the relationship between shredding conditions, safety, and recyclability Characterising, separating, and purifying, cells, cell components, and black
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Background To create and contribute to the creation of knowledge by undertaking a specified range of activities within the research programme of the Elementary Particle Physics Group. To work on detector
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-institutional strategic national research programme dedicated to using data to transform our understanding of cancer risk and enable early interception of cancers. It represents a major, multi-million-pound
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Full Time, Fixed Term contract up to May 2029 Closing date: 14th April 2026 Background CHASM is a multidisciplinary research centre for financial security, wellbeing and inclusion. We produce research
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during