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exploring B cell migration in the spleen. The successful candidate will have extensive experience in handling and processing live spleens and an established expertise in live imaging of this organ. As a
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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on process development, electrode manufacture and performance assessment, but depending on the skills of the successful applicant, may also involve some aspects of modelling or data science. The post is funded
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at the intersection of these research areas. You should hold, or be close to completing, a PhD/DPhil in mathematics, statistics, physics, engineering, data science, or a related field. Experience in cancer
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instrumentation package. • Implement real-time signal processing and post-processing techniques to improve recording fidelity. • Design and test hardware on the bench to ensure robustness prior
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providing intellectual support and technical advice on projects and in assisting others in tools relating to data processing and analysis. A forward-thinking, collaborative approach to research will be
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expected that the successful candidate will contribute to the computational analysis of multi-omic data that will be generated during the project. The candidate must hold or be near completion to a PhD/DPhil
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type (iv) work with the computational biology team to transfer this information into a AI algorithm that can distinguish neurodegenerative and neuroprotective phenotypes (v) work with colleagues in
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- the English Case Study investigating SSVS pilot project courts. This includes data collection, including court observation and participants interviews, coding and analysis of data, the development of project