510 parallel-processing-bioinformatics uni jobs at University of Oxford in United Kingdom
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About the role The Sample Handling Laboratory in the Cancer and Haematology Centre, Churchill Hospital, Oxford processes patient samples from cancer clinical trials. The role of the post holder is
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experience in print, digital and social media and in producing effective web content. You are expected to have excellent IT skills; proficiency working with a range of computer-based and online applications
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leave schemes • Cycle loan scheme • Discounted bus travel and Season Ticket travel loans Committed to equality and valuing diversity Application process You will be required to upload your CV
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draw on your numeracy and IT skills, pro-actively improving the administration of your scholarships and enabling them to keep on making a positive difference to our students’ lives. Application Process
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and flexible working can be considered. Diversity Committed to equality and valuing diversity. Application Process You will be required to upload a supporting statement and an up-to-date CV as part of
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, blood sampling and processing. They will support study co-ordinators and principle investigators, contributing to the set-up and co-ordination of new studies and take responsibility for a small portfolio
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and events. Contributing to the development of new initiatives and continuous improvement of existing ones. Implementing standardised processes and programme policies. Supporting consultants and
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colleagues and project teams on data management processes. Liaising with internal and external stakeholders to gather and verify information. Contributing to the development and improvement of monitoring and
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-based design and simulation, and as such the successful candidate will be an expert in the use of CAD programs (i.e. SOLIDWORKS/AutoCAD), design for manufacture techniques, network models and
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architectures to enable near real-time 3D reconstruction from 2D ultrasound video. The post-holder will contribute to cutting-edge research at the intersection of deep learning, computer vision, and biomedical