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https://www.sems.qmul.ac.uk/research/studentships/674/net-zero-natural-resource-energy-and-time-efficient-manufacturing/The PhD work will benefit from access to unique facilities including
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. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in 2D convolutional neural networks in Python. This is a part-time position (5
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(SFDI) and also from our custom-built photoplethysmography (PPG) sensor. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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opportunity for a highly motivated and skilled Research Associate/Assistant in statistics to join the EPSRC funded project PINCODE: Pooling INference and COmbining Distributions Exactly: A Bayesian Approach
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to a net zero economy, electrical power systems are rapidly decarbonizing supply whilst electrifying carbon-intensive demand. There is therefore an acceleration in the connection of low carbon
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | 18 days ago
communication skills with experience in presenting research, writing study protocols, and drafting strategic papers and manuscripts for publication. Actively build and maintain a network of colleagues and
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interest in expanding their knowledge in both domains. (1) Geometry/Topology -related methods in computer science. (2) Machine Learning. (For example, graph neural networks, generative networks, or neural
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position (2 + 2 model) under the supervision of Sebastian Szyller. Trustworthy & Adversarial Computing Lab is a newly established group. The lab has an extensive network consisting of companies and academic
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of Liverpool, and Prof James Chalmers at the University of Dundee. You will be sited within the vibrant research environment of the School of Biosciences but will work closely with the collaborative network