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experiments and numerical simulations to understand and predict the clogging evolution in a range of geological media by: Quantifying physical and chemical clogging dynamics across a spectrum of rock types
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systematic investigation across diverse rock types and integration with predictive models remains lacking. In this PhD study, you will be performing experiments and numerical simulations to understand and
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, or similar; strong programming skills (Python or similar); affinity with spatiotemporal data analyses, remote sensing and numerical modelling; the ability to independently plan and organise the research, and
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your PhD you will develop a range of research-focused and broader academic skills, including: Volumetric imaging: perform experiments using a light-sheet microscope optimized for live, volumetric imaging
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with spatiotemporal data analyses, remote sensing and numerical modelling; the ability to independently plan and organise the research, and to take a leading role in its direction; strong oral and
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antibodies) from individual serum samples. You will further develop and optimize these methods, with as special aim to enrich for antigen-specific antibodies. A secondary key objective is to improve
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from a wide-range of disciplines in future climate model development, paleo-climate data collection, and applied mathematics. Your qualities The project requires the development of both numerical skills
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, and engineering to optimize and upscale and biodegradable structures that temporarily mimic key emergent traits using industrial-scale additive manufacturing (i.e., 3D-printing) techniques
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. You will build on our recently developed single-cell ribosome profiling methods for C. elegans and further optimize them to apply to the early embryo. With this approach, you will generate a genome-wide
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. First, you will help build a light-sheet microscope optimized for voltage imaging at the single-cell and subcellular level in live larval zebrafish. The development of this system will be supported by Dr