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Applications are invited for two Research Assistant / Research Associate posts on the project EQUATE - a project that investigates how Natural Language Processing (NLP) could be made globally more
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discovery process, leading to more economic and effective drugs that can significantly improve the health and lifestyle of millions. The resulting methods are also expected to have an impact in materials
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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holder will be required to have practical experience in high-density microelectrode pattern on soft substrates with good understanding of advanced microfabrication processes, electrode substrate
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relating to the role ( andrew.dunning@bodleian.ox.ac.uk ). General queries about the recruitment and application process should be directed to the Recruitment team ( recruitment@glam.ox.ac.uk ). Only
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process It is anticipated that the selection process will take place on 8th July. This will consist of an interview, test and tour. We plan to let candidates know if they have progressed to the selection
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. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Further information We pride ourselves on being inclusive and welcoming. We embrace diversity and
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about this vacancy Prof Ioannis Brilakis, ib340@cam.ac.uk may be the contact for queries of a technical nature related to the role or the application process, please contact: Ms Rachel Judson, email
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://hr.admin.ox.ac.uk/staff-benefits Application Process Applications for this vacancy are to be made online. You will be required to upload a Supporting Statement and CV as part of your online application. Either using
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processes. Carbonate biomineralisation is a key process in global carbon cycling, but there are major gaps in our understanding of how biominerals form. We lack a quantitative understanding that can predict