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a relevant field and have strong quantitative and analytical skills, including experience in food systems modelling or closely related areas. Proficiency in data analysis and coding (e.g. Python, R
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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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), computing sensitivity kernels and applying the BG-SOLA method to infer the properties of the MTZ. They will adapt existing and develop new seismic analysis and inverse methodologies within a finite-frequency
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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