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applications (e.g. natural language processing, multivariate time-series data), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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with a disability, we are committed to ensuring fair treatment throughout the recruitment process. We will make adjustments to support the interview process wherever it is reasonable to do so and, where
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. 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 their thesis and are
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skills and proficient in the use of applications such as Microsoft Word, Excel, PowerPoint. Experience in preparing high-quality manuscripts and submitting them for publication in academic journals
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about this position may be directed to Dr Ali Meghji Email: am2059@cam.ac.uk If you have any queries regarding the application process, please contact: hr@hsps.cam.ac.uk Please quote reference JM46722
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this position may be directed to Dr Ali Meghji Email: am2059@cam.ac.uk If you have any queries regarding the application process, please contact: hr@hsps.cam.ac.uk Please quote reference JM46722 on your
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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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behaviour of so-called yield stress fluids, which keep their shape like solids at low loads, yet flow like a liquid at larger loads. One possible focus could be on the dynamical process whereby a material in
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or of connectome analysis and of insect neural circuits will be highly desirable. Successful candidates will join a team based in Zoology with 15 team members, carrying out data processing and computational analysis