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Raman’s cardiovascular research team. This role is embedded within a cutting-edge programme focused on integrating high-dimensional datasets, including advanced cardiac MRI (oxygen-sensitive, metabolic, and
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We are seeking to appoint a Research Assistant for the pre-erythrocytic malaria vaccine development programme led by Professor Adrian Hill. You will be responsible for performing immunological
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computing and associated increases power demand and procurement costs. This role will support the creation of a network of experts, a team of champions and a portfolio of community projects to provide UKRI
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the University of Oxford, the postholder will conduct scientific research that refines existing methods, sheds light on the impacts of climate change in understudied regions, and informs adaptation and legal
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of ethnographic or collaborative methods, as well as contributing to peer reviewed publications/presentations. You will also have excellent organisational skills and the ability to communicate effectively with
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competence is expected in the use of analytical methods including proton NMR spectroscopy and mass spectrometry for reaction monitoring. Ideally candidates will also be experienced in synthetic organic
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ultimately contributing to the development of new antiviral approaches. The project takes a cross-disciplinary approach, combining biochemical, biophysical, cell biological, and virological methods, including
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Mobility Reading Group led by Nobuko Yoshida. The successful candidate will be located in the Department of Computer Science Reporting to Professor Nobuko Yoshida, the post holder will be responsible
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Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
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reconciliation, enhancement, and integration of the MLGB dataset, working with legacy print, manuscript, and digital sources. You will apply and adapt digital methods (especially TEI XML), analyse provenance data