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“Health Passport” system for railway tracks on bridges, enabling data-driven condition assessment and supporting more efficient maintenance and asset management strategies. The project aims to develop a
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Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable
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to enable indirect and frequent assessments of railway embankment conditions. Using measurement data collected by the CTO monitoring train in the Netherlands, the research will examine the relationships
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under budget constraints. Apart from the research project, the candidate is expected to contribute (10% of total workload) to the teaching and supervision of Bachelor and Master students. Where to apply
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Networks Our goal: to develop recyclable, non-persistent thermoset resins based on humins, creating more sustainable alternatives for conventional materials. Your colleagues: The project is part of the NWO
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to e‑wax), and long-term stability. By combining advanced kinetic studies with state-of-the-art operando characterization techniques, you will develop fundamental insights that enable improved catalyst
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to technical, legal and organizational constraints. As a PhD candidate, you will develop novel decision-making methods that enable robust decisions for heat transition planning despite these data-sharing
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future energy applications. Rather than simply implementing existing data space reference architectures, you will develop novel methods, architectural patterns, and engineering approaches that enable
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countries. Best of all, you will not do this alone: you will be part of a vibrant, international cohort of 11 doctoral candidates who train, travel, and tackle the challenges of quantum-secure communication
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motivated PhD candidate to develop next-generation one-way transparent optical films based on liquid crystal polymer technology. The position is embedded in the research group of Dr. Danqing Liu at Eindhoven