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of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real robots
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tools. As the successful candidate you will focus on developing theoretical models and inference tools to understand dynamic processes within and between cortical organoids. This involves integrating
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research group has shown, by contrast, that the dynamics of antigenically diverse pathogens is driven by naturally acquired immunity against epitopes of limited variability (ELV), thereby opening up
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-funded Strategic Longer and Larger (sLoLa) research programme entitled “An integrated analysis of S-acylation dynamics and its importance in cell physiology.” This collaborative, multidisciplinary project
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that all epitopes under strong immune selection are inevitably highly variable. Our research group has shown, by contrast, that the dynamics of antigenically diverse pathogens is driven by naturally acquired
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electrochemistry. Our goal is to combine electronic structure theory, molecular and quantum dynamics methodology, and machine learning methods to achieve an accurate yet computationally feasible description
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The University of Oxford is a stimulating work environment, which enjoys an international reputation as a world-class centre of excellence. Our research plays a key role in tackling many global
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System Models, or related simulation tools. Additional knowledge of statistical methods, Monte Carlo techniques, or ensemble approaches is highly valued. The post is advertised as full-time. We are open to
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The School of Life Sciences at the University of Dundee is a world-class academic institution with a reputation for the excellence of its research, its high quality teaching and student experience
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, genetic, and DNA methylation analyses to patient-derived samples and disease models. Working closely with a dynamic and multidisciplinary team of clinicians and scientists, they will help generate and