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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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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
of tropical forests in the Amazon and on how these relate to the distribution of vector-borne diseases in the Amazon forest. The post holder will carry out their research, advised by the PI and Dr. Milton
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the Faculties of Linguistics, Philology, and Phonetics and Modern Languages. Division of time between the two Faculties to be flexibly distributed according to contingencies, as determined by the IT Manager
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calendars, the preparation and distribution of agendas and taking, transcription and distribution of minutes, and follow up of action points arising from meetings. You will be educated to at least A-Level
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software development in a team setting • Experience with version control distribution software like Git • Experience with numerical methods and techniques, including optimization and statistical analysis
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. This is part of an EPSRC-funded project on Algorithmic Comparison of Stochastic Systems. The post holder will work closely with the Principal Investigator, Stefan Kiefer, but also with other members of a
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Join Oxford Digital Health Labs as a Senior Research Scientist or Software Engineer, where you will play a pivotal role in developing advanced algorithms for cardiotocography and fetal ECG analysis
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. Armed with this information, the post holder will use cutting-edge paleoclimatic modelling that incorporates nutrient cycling and carbon chemistry (HadOCC) to infer the distribution of potential feeding
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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods