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. The candidate will conduct research in archives. Based on an analysis of source material, the strategies developed to reconcile the interests of multiple bondholders will be examined. Specific attention will be
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-tracking, pupillometry), cognitive modelling, and regulatory analysis to assess how algorithmic explanations shape human judgement and how existing legal and ethical frameworks align with the evolution
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in vivo and in vitro approaches to study maternal mRNA regulation across multiple levels. Zebrafish is our primary in vivo model, offering powerful genetic tools and abundant embryos for applications
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interdisciplinary, and there are multiple aspects to it that one or two different persons can fill with different interests/backgrounds. In all cases, extensive project training will be provided. Candidates with
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of
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novel multi-objective optimisation algorithms, to evaluate metrics such as material circularity, system efficiency, cost, and carbon footprint. The University of Surrey is ranked 12th in the UK in
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novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable
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will design quantum-safe threshold encryption and/or authentication algorithms. The expected outcome is the design of methods, techniques and their software prototype to implement quantum-safe threshold