72 ability-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at University of Oxford
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programming skills, such as Python, excellent organisational and record-keeping skills, and the ability to communicate research clearly through publications, presentations and collaborative work are essential
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publications and conference presentations is essential, as is the ability to communicate complex technical concepts clearly and effectively to a range of audiences. We are looking for candidates who can
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opportunity, and to being a place where everyone belongs and is supported to succeed. We recognise how the diversity of our community enriches our ability to deliver on our academic mission. We welcome
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-genome sequencing. You will possess strong analytical, problem-solving, and data interpretation skills, with the ability to work both independently and collaboratively within a multidisciplinary research
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with the gonococcus. You should be able to maintain accurate and detailed records and have experience using LabArchives software. Excellent communication skills, as well as the ability to effectively
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experience using statistical software such as R, Stata or Python, together with the ability to manage and analyse complex datasets and contribute to scientific publications and presentations. You will also
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belongs and is supported to succeed. We recognise how the diversity of our community enriches our ability to deliver on our academic mission. We welcome applications from individuals from all backgrounds
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including statistical programming (e.g., STATA, RStudio, Python). You will demonstrate previous experience of contributing to publications/presentations as well as the ability to manage your own academic
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collaborative skills are essential, including the ability to work effectively with immunologists, clinicians, microbiologists, statisticians, data scientists and AI specialists and to represent the research group
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substantial experience of machine learning in a research or industry environment, and have the ability and willingness to combine machine learning research with sustained engagement with historical and