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stakeholders. You will also contribute to other collaborative research e.g. conducting evidence synthesis using a range of approaches (e.g. systematic reviews, scoping reviews, network meta-analysis). There will
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-world interventions. A key part of this role will be performing systematic literature searches and meta-analyses of dose–response and exposure–response data to support model calibration and uncertainty
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searches and meta-analyses of dose–response and exposure–response data to support model calibration and uncertainty analysis. This role offers a rare opportunity to bridge public health and building science
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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Job Reference: 1168098 About the Role: You will play a key role in advancing distributed and adaptive AI methods, focusing on scalable software frameworks, learning algorithms, and orchestration
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closely with the Epidemiology Large Data Review Group, conducting advanced statistical analyses in Python, R, and Stata, and leading systematic and Bayesian meta-analyses. The role also includes weekly
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education sector Highly desirable: experience with data linkage techniques use of health service data familiarity with government data assets (e.g., PLIDA, National Disability Data Asset) experience with meta
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for full-time or part-time employment in a European research program in the field of " Photonics for Quantum Key Distribution". The successful candidate(s) will work on a €7.5 million research project
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efficient numerical methods for solving the problems, and implement the numerical algorithms to verify the theoretical results. Job Requirements: Applicants should possess a PhD degree or have satisfied all
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women. Perform advanced statistical analysis of cohort studies and meta-analysis of published literature to achieve project outcomes specified in the project work plan. Prepare applications for data