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and active contribution to the principles of the ‘Sheffield Academic’. These include the achievement of excellence in applied teaching and research, and scholarly pursuits to make a genuine difference
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stimulation, using custom cryo-plunging and high-pressure freezing instruments. In parallel, we are working to achieve multicolor electron imaging via cathodoluminescence—electron-beam–induced optical emission
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parallel screening platform to discover orthogonal protein binders. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing
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developments by the project team regarding advanced crystal plasticity models, different modeling strategies will be explored, including strain gradient plasticity [1,8,9], micromorphic approaches [2], and
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strategies for large-scale or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data pipelines for high
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developments by the project team regarding advanced crystal plasticity models, different modeling strategies will be explored, including strain gradient plasticity [1,8,9], micromorphic approaches [2], and
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to enable quantitative, high-resolution, time-lapse monitoring of soil properties and will be implemented using high-performance parallel computing. This PhD position offers the opportunity to work at the
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chronic disease, stress may actively contribute to disease onset and progression through complex biological mechanisms. This PhD project aims to decipher how different forms of stress influence inflammatory
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signals are required for C. difficile germination. In nutrient-rich media, genetically identical spores germinate at different times, but in presence of bile salts—exclusively found in the gut—spores
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trends and produce meaningful data visualisations, as well as experience of working with different bioinformatics tools and statistical methods. The applicant is expected to leverage multi-modal data