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numerical methods for the inverse design of nanophotonic structures enabling broadband, multiparameter sensing in fiber-based systems. The project is a collaboration between AMOLF, TU Eindhoven, and
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builds on our recent works (https://www.nature.com/articles/s41467-025-65282-1 and https://www.nature.com/articles/nature20605 ). Join our team in the https://pomplunlab.com and https
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Circuits Project description: Neuronal synapses are remarkably heterogeneous and dynamic structures that vary widely in molecular composition, nanostructure, and signaling strength. This rich variety
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relationships on specific indicators for these quantities, you will obtain a set of equations that describe ecosystem structure and functioning as a function of size and other relevant properties. You will test
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. The result is a new class of living composite materials that are not only structurally resilient but also inherently sustainable, moving us toward a future where infrastructure is grown, not just built
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require new metrics, fast algorithms, and careful tailoring of commonly used network measures and algorithms. The aim is to advance our understanding of how social network structures change over time due
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, with a focus on crack initiation, propagation, and damage evolution. These structures are characterised by large wall thicknesses, irregular bond patterns, varying material quality, and exposure
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performance and/or neural structure/function that govern the rate of cognitive development in childhood and/or old age. The post holder will have an interest in theory-based developmental cognitive (neuro
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structures and activities. The postdoc will lead the compilation, annotation, and integration of microbial volatile data, linking metabolomic profiles to microbial genomes, traits and ecological functions
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consortium, translating complex CFD results into actionable insights for structural and control engineers. Where to apply Website https://www.academictransfer.com/en/jobs/359872/postdoctoral-researcher-high-fi