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About the Role The position is funded through the EPSRC project “Zeros, Algorithms, and Correlation for graph polynomials”. We study various combinatorially defined polynomials such as the
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to trace how welfare algorithms operate in practice. They will also contribute to comparative analysis across case study countries, support interdisciplinary collaboration, engage with external stakeholders
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search strategies and lexicons. Proficiency in fitting and validating statistical models or machine learning algorithms is essential, along with advanced skills in R and/or Python for data processing and
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the design, development, deployment and evaluation of NeoShield’s applied machine-learning systems, the machine-learning-driven Clinical Decision Support Algorithm for neonatal sepsis and the real-time ward