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collaborative research investigating host–microbiome interactions and their impact on postnatal growth and metabolism in preterm infants. • Design, perform, and interpret experiments using mouse models, molecular
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over time. Building on these findings, the project will quantify how different patterns of missingness may impact risk prediction model performance and calibration. Novel methods will be developed
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biodiversity. NaviSense performs research in the areas of (1) animal navigation mechanisms and their underlying senses, (2) quantum effects at ambient temperature in model systems and biology, (3) ecological and
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. The DWELLWELL project will involve two PhD-candidates working with different methods on different research questions. While housing is recognized as an important social determinant of health, this relationship is
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for operational decision‑making, interactive design, or control‑in‑the‑loop visualisation. Machine‑learning surrogates offer speed, yet purely data‑driven models often extrapolate poorly and may violate physical
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system perform well. This PhD project aims to answer this question. You will develop a unified mathematical theory and framework to study and explain how different reservoir systems work and how to design
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ponds of different types and ecological quality, by implementing an integrative approach using conventional, molecular and computational tools to generate a dataset that spans multiple trophic layers
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to reach consensus on mental health priorities with different key groups. Policy briefs will translate these findings for policymakers, voluntary organisations, and advocacy groups across the island
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biological mechanisms is necessary to establish mechanistic models for tree distribution and growth that will improve our predictions of tree species' range-shifts as well as productivity changes within
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antibiotic resistance. Until now, cytochrome bd structures from from four different species (E. Coli, Mycobacterium smegmatis, Mycobacterium tuberculosis et Corynebacterium glutamicum) are available. The first