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Field
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materials are connected is critical for the development of next generation functional materials. However, modern atomically-resolved imaging techniques only give an integrated snapshot of the structure
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diffraction tomography (ODT). The ODT will be used for imaging organoids and a correlative fluorescence microscopy must be integrated with the ODT. A close cooperation with COMBAT partners associated with WP 2
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their evolution during catalytic operation and activation. You will apply advanced electron diffraction techniques (3DED, 4D-STEM tomography), atomic resolution STEM imaging (HAADF, ABF), EDX and EELS
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characterizations of additive-manufactured and heat-treated steels, using state-of-the-art methods such as scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), X-ray diffraction (XRD), and
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of systems biology, virology, high-throughput genetics, genomics and proteomics, molecular and cell biology, high content automatic imaging, chemical biology, and organic chemical synthesis. The program Our
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persists, even for the most powerful sensors operating in this way. A drastic departure from this sensing architecture is “multistatic” radar – enacted by a coherent network of spatially distributed sensors
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to research this topic. Interest in laboratory work and basic technical understanding. Fluent written and spoken English. Programming skills in e.g. Python, R, Matlab and Java. Experience in image processing
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. The project will combine field measurements and laboratory analysis, using cutting-edge techniques including dynamic contact angle measurement, X-ray diffraction, mid-infrared spectroscopy, and synchrotron
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the pH range of 2.5 to 4.5. Advanced analytical training will be provided in techniques such as X-ray Diffraction (XRD), synchrotron-based spectroscopy and scanning electron microscopy (SEM). This PhD
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techniques (e.g. electron microscopy) will then be applied to assess the extent of material degradation in each case. Characterisation could include in-situ tensile testing coupled with digital image