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of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience of C/C++/C#, TensorFlow would be beneficial
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opportunity for an enthusiastic and motivated postdoctoral fellow in data-sciences and biomedical informatics to work on exciting human and veterinary health studies, such as the identification of novel
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. The successful candidate will join a large and diverse group of researchers covering nuclear structure physics, nuclear astrophysics, applications of nuclear physics and nuclear theory. The candidate's programme
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programme This project focuses on the application of digital health technology to study the contribution of sleep and circadian disturbance to brain function, neuropsychiatric symptoms and behaviour in people
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language data taken from multiple sources: ongoing fieldwork, previous studies, text corpora and newly-generated reconstructions, as well as well as the results of computational simulations and artificial
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you You should have a PhD (or be close to completing a PhD) in a relevant social science discipline or have equivalent relevant professional experience. You should have experience of using qualitative
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. About you The successful candidate will have a strong background in experimental testing, programming (MATLAB/SIMULINK) and control, and should have a PhD in a relevant discipline such as mechanical
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Environment Research Council (NERC) at the University of Surrey. Accurately measuring greenhouse gas emissions from human activity is challenging. Static sensors only measure one point in space, but sensors
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support oncology staff to engage with, communicate and act on mainstreaming genomic testing information. This review will lead to evidence based recommendations and targeted outputs which may generate