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Project description This project is part of the MSCA Doctoral Networks program e-ChemIn, connecting 10 research institutes and 3 companies across Europe in a joint effort to identify design
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bottom and fly ash residues and can spread persistent contaminants. This leaves a major gap: how to valorize low-grade waste into high-value products beyond biofuels/biogas at industrially-relevant scales
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high-density 3D Multi-Electrode Arrays (3D-MEAs) — done in close collaboration with experts, providing full support as you learn to analyze this data. o Multi-Omic Profiling: Performing and analyzing
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of high-performance computer systems You preferably have experience with hydrology, and affinity or experience with agent-based modelling and large-scale data processing with societal relevance You are able
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, reliability, and operational performance. As railway infrastructure ages and traffic demands increase, there is a growing need for innovative methods to continuously assess track condition and predict
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flows. This project is part of the Holland High Tech program, and you will closely collaborate with our industrial partners (M2i, Tata Steel). Job requirements You are a recent graduate looking to use
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nanoparticle performance. Develop formulation strategies that balance: Mechanical robustness (required for purification and storage) Ultrasound responsiveness for triggered drug release Computational simulations
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description How can spin wave show quantum properties and how are they useful
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PhD Position Simulating the Airspace of the Future: Fleet & Network Optimization for Future Aircraft
) Application Deadline 30 Aug 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not
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Help decode the microbial nitrogen cycle for a more sustainable future. As a PhD candidate, you will combine experimental and computational approaches to uncover how microbial communities drive