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collaboration with a PhD candidate at the Methods and Statistics department, for example on complex data analysis, and the development of personalised visualisations for use by clinicians and patients. You also
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predictive modelling. The project gives you the opportunity to work across scales: from thousands of plants and complex microbiome datasets to mechanistic experiments with individual microbial isolates. Your
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Institute of Physics that focuses on complex fluids and soft mesoscopic materials, both experimentally and computationally. There are strong links with soft condensed‑matter theory and computational chemistry
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metrology tools is continuously challenged by stricter requirements and increasingly complex geometries. In this project, you will work on the ideation, modeling, and experimental validation of novel
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to understand how complex biological functions emerge from interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362789/phd-learning-interactions-in-co
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advanced algorithms for solving complex optimization problems. You will work with real-world case studies to design future-proof supply chain networks for key agricultural products in vulnerable regions
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Are you eager to push optical atomic clocks to new levels in a lively, international research group? Do you enjoy creating complex machines that have never existed before? Do you want to explore
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interact with complex glycans and how receptor binding evolves across strains and host species. Depending on your background and interests, you will contribute through complementary approaches such as
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clearly, and are motivated to analyse complex spectroscopic data and connect these results to molecular processes. Strong initiative and passion for science Open to collaborate with students (BSc/MSc), PhDs
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(e.g. VAE, UMAP, surrogate models). Working carefully and reproducibly, document simulation conditions and results clearly, and are motivated to analyse complex data and connect these results