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. This interdisciplinary collaboration with the University of Lincoln and University of Liverpool focuses on developing innovative computational approaches that integrate advanced genomic analysis with state-of-the-art
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to candidates with a strong quantitative background. We welcome applicants with training in mathematics, statistics, health economics, computer science, or epidemiology, particularly those with good numeracy and
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. This interdisciplinary collaboration with the University of Lincoln and University of Liverpool focuses on developing innovative computational approaches that integrate advanced genomic analysis with state-of-the-art
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an ambitious programme combining collaborative work with health researchers and the development of novel statistical methods to address complex biomedical challenges. About the role The postholder will join the
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complex epilepsies using a multimodal approach, including clinical phenotyping, genomics, imaging, and other methodologies, with an emphasis on translational impact. About the role We have an exciting
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a state-of-the-art Earth system models(UKESM). We are looking for someone experienced in analysing output from large, complex climate models or Earth system datasets, and who is experienced in or keen
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. Hands-on expertise with microcontrollers (e.g. Arduino, STM32), embedded C/C++, and firmware development. Familiarity with BMS development or experience with other complex control systems such as motor
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-cell genomics/computer science (AI), neuroscience, vascular biology, developmental biology, cancer biology, immunology, biology/biomedicine, pharmacy, biomedical engineering, or related fields with ample
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It
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the Department of Inflammation and Ageing at the University of Birmingham. The successful candidate will work to deliver high level computational analysis of immune cell subsets in patients with cutaneous lupus