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hidden patterns from them? Do you enjoy exploring mathematical models and working with network data? Join our team! Job description Complex systems are often modeled with networks, structures where
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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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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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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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types that reflect related biological mechanisms, such as proteomics, metabolomics, and transcriptomics. Latent variable models are widely used for identifying the underlying structure in such high
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to cracking, corrosion, and a lack of structural redundancy. In the Netherlands, the safety of these structures depends on the integrity of the lower nibs. These are typically slab structures that are known as
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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
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model of the non-transparent structure. Using this approach, we aim to build a microscope that can look inside very complex materials without loss of image quality. Your role is to build flexible 3-D ray
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we’re growing along with it. At the Universiteit Maastricht (UM), your work makes a difference—whether you explore complex biological systems, contribute to cutting-edge research, or help shape
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acquired from the degradation in the solid phase obtained by PhD2. Specifically, you will: Build molecular networks based on both chemical structures and mass spectrometric (MS) data to unravel complex