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developing new approaches with genomics collaborators. We are seeking an individual with experience of processing and analysing genomic data using existing tools (e.g. EdgeR/DeSeq2 for RNAseq) and developing
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interaction (HCI), electronic engineering, design engineering, science and technology studies (STS), music composition/performance, musicology or anthropology. (E) Practical experience within a research
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teams to lead talent development, performance management (ARC), and succession planning processes. Develop a comprehensive curriculum for all people managers, empowering them to inspire and support our
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Applications are invited for a Research Associate* position in the intersection of machine learning and information theory. The successful candidates will be based within the Information Processing
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-intensive or similarly complex organisation. A demonstrable ability to create and implement new operational structures and processes. Exceptional people management and leadership skills, with a track record