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About us The School of Neuroscience is UK’s 2nd largest Neuroscience school with over 500 researchers and 200 PhD students. It is one of three schools at the Institute of Psychiatry, Psychology & Neuroscience. CDN is one of four departments in the School of Neuroscience at the Institute of...
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28 Aug 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Computer science Physics Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country United Kingdom Application Deadline 9 Sep 2025 - 00:00 (UTC) Type of Contract Other Job...
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coalitions for delivering reliable, low-carbon energy services. Collaborating closely with UK Power Networks, SSE Energy Solutions, and the University of East London, you will develop robust economic Model
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Applications are invited for a fully funded fixed-term position at the Research Associate (PostDoc) level in de-risking cirrus modification. Cirrus cloud modification (CCM) could in-theory mitigate
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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marginal structural models will be extended with machine learning techniques for counterfactual prediction and to support sensitivity analyses Candidate The studentship is suited to a candidate with a strong
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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verification methodology and corresponding toolchain to detect and mitigate such threats to CPS at the design time making the CPS resilient-by-design. Typically, CPS are modelled as hybrid systems, comprising
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for downstream tasks. In this project, you will develop novel unsupervised machine learning methods to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a