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will play a pivotal role in developing advanced algorithms for cardiotocography and fetal ECG analysis. In this position, you will manage and innovate next-generation algorithms, focusing on both
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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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, including meta-analysis using PLINK 1.9 (fixed-effects inverse-variance model), conditional analysis using REGENIE, and fine-mapping of HLA–protein associations. You must hold a first degree in Genomic
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for someone with understanding of public health research designs, in particular longitudinal surveys, randomised controlled trials and systematic reviews/meta-analyses; and skills in data cleaning and
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Felipe Thomaz. FOMI currently has an active group of corporate partners, including BMC Software, Diageo, Google, Institute of Real Growth, Kantar Group, L’Oréal, Mars, Meta, Reckitt, Unilever
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. The postholder will help lead a project work package
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leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis of normative frameworks and aggregation rules, and
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aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will support the development