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structure–property relationships in metal halide perovskites at an atomistic level”. This collaborative project will establish structure-property relationships in hybrid metal-halide semiconductors
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About the role We are seeking an outstanding candidate to work in the Process Dynamics group to contribute to advanced research in AI-driven X-ray imaging for metal alloy solidification
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are flexible, but September – October 2026 is preferred. The successful candidates will be members of the Centre for Topological Data Analysis with responsibility for carrying out research in applied
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) from Tanzania, working closely with colleagues at the University of Dar es Salaam. Returned samples will be analysed by the postholder for their noble gas isotopic composition and trace gas abundance
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bacteriological studies using a range of approaches including protein purification, in vitro and cellular protein characterization, proteomics, and high throughput genetic analysis. Structural studies will be
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. With a background in testing of materials and numerical analysis, you will be self-motivated, able to plan and deliver a research project. You will have a PhD (or be near completion) in related topics
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Moore. You will be responsible for adapting existing mathematical and statistical methods for analysis of high-dimensional imaging data, and analysing quantitative imaging data from a variety of sources
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Technology. Additional Actions : Composite Materials, Finite Element Modelling (FEM), Impact Engineering, High-Rate Experimental Mechanics, AI Assisted Surrogate Modelling
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reactions, along with constitutive models for glassy and semi-crystalline biodegradable polymers, building on recent works from the Brassart group. You will implement the models in a finite element software
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role focuses on the computational analysis and methodological development of third-generation and single-cell sequencing data to understand the role of transposable elements (TEs) in early mammalian