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, engaging with students, academic Module Organisers, teaching teams and Programme Directors. About You You will be educated to degree level or equivalent and have relevant experience of working in a higher
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care and preventive medicine. The post-holder will work in the Centre for Evaluation and Methods (CEM), a thriving centre that incorporates collaborative units who work to deliver outstanding research
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in managing the processes post-merger of 3 academic schools. The post holder will use project management methods to track and manage all processes of integration and formation of the new academic
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computational modelling and design optimisation. You will run CFD and fluid-structure-interaction simulations. You will develop models, analyse results and collaborate with partners to inform design. The role
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well as the employability programme at QMSU. The post holder will also support the wider Student Engagement Team’s work as and when required support the department with stakeholder management across QMSU and the University
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computational models of extra-chromosomal DNA in human cancers. Extra-chromosomal DNA drives some of the most difficult-to-treat cancers. Yet, little is known about the evolutionary process of ecDNA. This project
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, to deliver the aims of the programme. The PDRA will join a team working on extracellular vesicles as well as other aspects of inflammation resolution, with close attention to the exploit this science for
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, administratively support in-person examinations and prepare papers, support checking quality assurance information, work methodically, follow set processes and procedures and have a high level of attention to detail
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About the Role This role sits within the Faculty Student Experience Team and is the first point of contact for all student support queries for taught programme students in their cluster, handling
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research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models