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weekly attendance registers and monitor timely submissions, and Follow up with absent students and issue formal attendance warnings where appropriate, and Provide attendance data to support the academic
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& Performance department, we provide data, insight and advice that inform the direction and priorities of the institution. We’re looking for a Market and Portfolio Insight Lead to deliver clear, evidence-based
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the Lymphovascular Research group collaborating with computational, clinical and laboratory scientists. The post holder will support the group by analysing genomic data to identify and characterise genes underlying
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agreed by your current line manager. Interviews for this position will take place on 25th March 2026 Background Libraries and Learning Resources supports the information resource and service needs of staff
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at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information on our website. This post is
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clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information on our website. This post is available until 30 November 2028
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; microprocessor technologies; hardware systems for signal processing; novel computer architecture implementations; Compute-in-Memory circuits, and digital system-on-chips (SoC) implementations. Demonstrated
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communication, or stakeholder-coordination activities. They will also have working knowledge of ethical, data-protection, and compliance requirements relevant to research communication, including GDPR. For more
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assays, nucleic acid sequencing and analysis. You will hold an undergraduate degree in biomedical sciences with a working knowledge of data analysis including statistical analysis of data. Experience
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research project investigating the computational and neural principles by which multimodal information is encoded and combined in human perception. The research will combine computational modelling with