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Field
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recordings in vivo in rodents, as well as experience in the analysis of Electrophysiological signals. This is a full-time position and you will be offered a fixed term contract until the 1st September 2027
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. We are still far from a complete understanding of how these processes work. CDN is one of four departments in the School of Neuroscience at the Institute of Psychiatry, Psychology & Neuroscience and is
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“Apply Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have submitted
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at est42@cam.ac.uk . For queries relating to the application process, please email LE46553@maths.cam.ac.uk . Please indicate the contact details of two academic referees on the online application form and
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the volcanoes of the Eastern Caribbean as a focal point and, with our international partners, will demonstrate how this knowledge can improve monitoring and warning systems in the Eastern Caribbean. The
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combination of classical signal processing methods with state-of-the-art machine learning techniques, and you will thus find yourself in the intersection between emerging research domains and innovations, where
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to Professor Guilio Del Zanna at gd232@cam.ac.uk If you have any queries regarding the application process, please contact LE46579@maths.cam.ac.uk Click the 'Apply' button below to register an account with our
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at ben.allanach.work@gmail.com . If you have any queries regarding the application process, please contact LE46560@maths.cam.ac.uk Limit of tenure: one year, the funds for this post are available until the end
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of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will
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between chromatin regulation and immune signaling in response to environmental stimuli. Exploring the role of chromatin-associated factors that cooperate with histone variants and identify potential small