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the magnetization will propagate without scattering and loss of energy. Such structures could potentially be a novel building block for future computer chips and more sustainable IT technologies. Your research will
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physics, stochastic processes, statistical inference, and epidemiology, with SARS-CoV-2 and influenza as key case studies. Your job In this project, you will develop a quantitative theory of evolution
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these processes, inform targeted in vitro experiments, and help design better biomaterials and TE strategies that harness mechanics and geometry. As a PhD candidate, you will adopt and extend in-house homogenized
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from this PhD project into an agent-based model. This model will be developed by other PhDs in the project team and simulates household adaptation behaviour over time in global flood-prone regions
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of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after
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predictive theory for rapidly evolving viruses. You will work at the interface of theoretical physics, stochastic processes, statistical inference, and epidemiology, with SARS-CoV-2 and influenza as key case
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tools Computer science » Programming Engineering » Biomedical engineering Engineering » Simulation engineering Researcher Profile First Stage Researcher (R1) Application Deadline 30 Apr 2026 - 21:59 (UTC
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support systems, specifically simulation games and geospatial digital twins. These systems use detailed representations of a real-world environment and its processes by linking to a myriad of data and
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of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate
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PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline