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partners to ensure alignment of research goals with user needs. This is a full-time post, and you will be offered an a fixed term contract for a duration of 23 months. The desirable start date is October
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. The post will be based in the research team of Professor Katie Meehan at KCL’s Strand Campus in central London. About the role The Department of Geography at King’s College London invites applications for a
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. The post will be based in the research team of Professor Katie Meehan at KCL’s Strand Campus in central London. About the role The Department of Geography at King’s College London invites applications for a
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partners to ensure alignment of research goals with user needs. This is a full-time post, and you will be offered an a fixed term contract for a duration of 23 months. The desirable start date is October
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project partners such as WRAP, the Southeast Rivers Trust, the Wye and Usk Foundation, and the North Essex Farm Cluster to ensure the practical application of research findings This is a full time post, and
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description is not exhaustive, and the role holder may be required to undertake other relevant duties commensurate with the grading of the post and its general responsibilities. Activities may be subject to
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populations in vivo Desirable criteria Background in mammalian cerebral cortex development Background in inhibitory neurons Downloading a copy of our Job Description Full details of the role and the skills
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research aims to develop new AI for shared human-AI decision-making in healthcare imaging. This post is focused on AI-assisted ultrasound guidance building on the group’s prior work on video and multi
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experiments in conjunction with a post-doc, and will be fully embedded into the lab group. This position is suitable for researchers with previous experience working with phage infectivity and resistance assays
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. Working closely with Janne Pott, a postdoctoral researcher in the group, the successful applicant will perform simulation studies as well as applied analyses of sex-differential and/or time-varying exposure