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. This work utilizes advanced epidemiological modelling combined with AI methods for adaptive rather than static surveillance design. This project is particularly exciting because it combines new advances in
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combined with AI methods for adaptive rather than static surveillance design. This project is particularly exciting because it combines new advances in methodologies with direct applications in public health
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and applying high-throughput experimental and analytical methods to investigate how environmental conditions and organic additives influence carbonate mineral formation. This will involve designing and
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invertebrate data to extant species. Results from model efforts will be used in formal Red List Assessments, in collaboration with the Marine Invertebrate Red List Authority at the Naturmuseum Senckenberg
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responsible for the design and testing of original machine-learning based methods for fetal heart biomarker discovery from the CAIFE image and video dataset. The full-time post is funded by InnoHK and is fixed
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temporal reasoning ultrasound AI tools. Thus, the work will involve both computational methods research and collaborating with clinical domain experts to design and evaluate models in simulated and real
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well as proven competence in programming methods in Python or similar languages, and evidence of working well as part of a multidisciplinary research team. Informal enquiries may be addressed to Professor Tingting
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will possess sufficient specialist knowledge in the discipline to work within established research programmes. This includes expertise in qualitative and/or mixed methods research, ideally in a primary
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spectroscopy methods (Operando XPS/XAS, Hard XPS) to probe the interfacial reactions occurring in Li-ion batteries. Further information about the research group can be found at: https://emi.materials.ox.ac.uk
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complemented by biochemical and, where appropriate, structural methods. The successful candidate will be expected to work independently while contributing conceptually to the overall research programme. This