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robotic sample retrieval system that will be able to obtain surface swabbing samples of critical infrastructure buildings for chemical or biological analysis. The cohort of PhD students are spread around
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spatial distributions of active phases across multiple length scales. The PhD student will collaborate with international partners to study the evolution of crystalline and amorphous domains in the hybrid
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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of techniques for the analysis of topological data. Targeted activities in the field of public relations are also planned. The activities will mainly be based at the Institute of Scientific Computing
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becomes a real challenge to uniquely extract information on their layer properties in order to understand and improve their performance. A way to “break the nanometric barrier” for structure analysis is to
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dynamic environmental conditions; Integrate empirical data analysis into conceptual models to investigate how altered conditions due to offshore wind farms may lead to broader ecological impact across
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network analysis of interactions between these features. These pipelines and computational tools will be used to integrate imaging and genetic data, and maps of myelin distribution in the cortical grey
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functioning [1]. Building on these insights, you will compile and standardise datasets of collective movement and collect new data from multiple species of freshwater fish. From these data, you will identify
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. You will be taught a range of skills to complement, drive and strengthen your research: life-cycle analysis, techno-economic analysis, digital and business skills, ethics etc. You will also undertake
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(bio-)chemistry, physics, and engineering expertise to study molecules and cells, taking advantage of optical and single-molecule imaging, molecular probes, molecular biology, and 'large' data analysis