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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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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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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
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consortium, translating complex CFD results into actionable insights for structural and control engineers. Information and application Please submit your application before May 1, 2026, using the "Apply now
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; Contribute to the development of machine-learning models for classification and routing of complex electrolyte mixtures; Translate experimental data into Digital Product Passport-compatible formats and
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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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postdoc to study how supply chains can stay resilient and meet regulatory demands, using system modeling and scenario analysis. Job description Supply chains are increasingly exposed to complex and
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that astrocytes use for interacting with synapses and to tune their function, in health and disease. The candidate will perform genetic manipulation of astrocytes to study their structural and functional