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clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information. Fixed term contract posts are available for the stated period
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experience with management and strategy research, economic modelling and statistical analyses are essential. Familiarity with data mining, machine learning and computation techniques, especially in the context
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. Teaching and research experience in Health Economics / Econometrics are highly desirable. Experience in quantitative data and statistical analyses (preferably with health-economic data) with modelling
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applications, while the candidate working on Deliverable 2 will apply theoretical physics and statistical methods to LISA data analysis. The work will be carried out under the supervision of Assoc. Prof. Germano
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of Paediatrics at the University of Oxford. The goal of our research is to understand the information that shapes the complex physical architecture of the heart wall, and how it can be disrupted to produce
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, e.g. surveys, literature reviews, data gathering and/or recording of results using appropriate research methods. Participate in and/or present at conferences and/or workshops relevant to the project as
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Information below for the full list of essential and desirable criteria. To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where
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comparing model predictions of observed transient data Experience in software development with larger scientific codes; in particular, expertise in Fortran, C, Python, and/or build systems are of advantage As
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PhD Research Fellow in Education: Learning, Readning, and Assessment in the Context of Generative AI
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with