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working will be considered. Contract type: Fixed term contract Fixed Term Period: For 24 months Salary: Full time starting salary is normally in the range of £37,337 to £41,478 per annum. Apply by: 19/08
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Fixed Term Contract for 24 months We welcome applications from passionate and skilled post-PhD or experienced researchers in malacology, epidemiology, schistosomiasis modelling, or spatial data
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
illnesses. The post holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning
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that influence global ocean mixing, heat and nutrient distribution, and climate dynamics. Despite their importance, these currents remain poorly understood due to their intermediate scale and intermittent nature
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, distributional impacts of policies, socio-economic modelling, or quantitative policy evaluation. Research with direct implications for public policy is preferred, particularly in areas related to energy, social
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, you supervise your students in courses about software architecture, software design, distributed systems engineering and software engineering. You are involved in organizing meetings, conferences and
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across the clade, and reconstruct geographic distributions of key nodes and fossil taxa. About you You will hold or be close to completion of a relevant PhD/DPhil, together with relevant experience. You
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computational tools to support the safe and ethical deployment of AI in clinical settings. The research focus is on AI performance monitoring, distribution shift detection, bias assessment, and stress testing
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to reconstruct the tree-of-life on Earth, it allows us to reveal how biological function has evolved and is distributed on this tree, and it is the foundation that enables us to use model organisms
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hydrometeorological and climatological) hazards, involving the quantification of effects on individual assets/infrastructure components (e.g., buildings) as well as network-level and distributed-system disruptions; 2