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inventory, a major incentive for the project is the application and adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases
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. Through our bachelor’s and master’s degrees, Professional Learning & Development programmes, and interdisciplinary research themes – including Emerging Technologies & Societal Transformations, Resilience
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science, human technology interaction, and machine learning. You will be working at the Human Media Interaction group in which computer science meets social science to investigate, design, and evaluate
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construct these species-specific mechanistic network models based on both genomic comparisons and machine learning based species-specific module identification. You will integrate these network models
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Science, Data Science, Artificial Intelligence or a related technical field. Experience and knowledgeable in AI techniques (e.g., machine learning, deep learning, predictive analytics) and data-driven approaches
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on studies of visual perception and decision-making. Research methods include computational modelling, brain imaging (fMRI), machine learning, behavioural methods, and other techniques. Virtually everything we
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adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases and in particular the complications encountered in photometric
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achieved through a variety of optimization, machine learning or AI-based heuristics. Optimization of revenue stacking models for hydrogen assets that have to supply a number of market-based services
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of political violence: from the role and effectiveness of sanctions during military disputes to the increasing importance of non-state actors in war, and from the effect of non-governmental organizations
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description A wealth of academic research has recently tackled new dimensions and aspects of political violence: from the role and effectiveness of sanctions during military disputes to the increasing