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Field
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affected families, or other similar marginalised groups Skills and attributes Ability to conduct qualitative research to a high standard, including data collection, developing an analytical approach, coding
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social care arena (eg: sociology; psychology; criminology; health statistics; health economics; data analytics, data science). Applicants should have experience of obtaining external funding for research
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excited by methodological innovation and real‑world impact. You will hold a PhD in a quantitative discipline such as infectious disease modelling, statistics, mathematical epidemiology, data science, or a
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part of a team developing analytic likelihood approximations and neural posterior estimation methods for epidemic data analysis. This role offers an excellent opportunity to work at the interface
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on patient care through improved diagnostic pipelines, integrative analytics, and data‑driven insight. As fitting with a Research Fellow or Senior Research Fellow, you will: Drive innovative research
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during
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equivalent qualifications High level analytical capability Ability to communicate complex information clearly Fluency in relevant models, techniques or methods and ability to contribute to developing new ones
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opportunities for collaboration. About You The candidate must have obtained a PhD degree within 3 years and in the relevant areas of business administration or data analytics, such as Applied Psychology
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Learning and Data Analytics. You will have experience in composing project deliverables and delivering effective presentations and be able to assist in project integration workshops and other meetings. With
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on understanding the aerodynamics and aeroacoustics of overlapping propeller systems. This project will involve high-fidelity flow and noise measurements, combined with semi-analytical predictive models