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resources efficiently. In this PhD project, you will develop mathematical theory and computational methods for the analysis and design of chaotic sampling mechanisms in networked control systems. You will
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contacts working at the front line of quantum computing, and a cross-disciplinary profile that remains rare and in high demand. You will be supervised by Dr Gabriele Liga (https://www.tue.nl/en/research
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procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop probabilistic digital twins of coronary arteries. The goal is to create patient-specific
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design possible in which even the small details can be readily incorporated into the electromagnetic model for robust performance analysis? Information Antenna and RF systems play a pivotal role in society
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network of peers, senior researchers and industry contacts working at the front line of quantum computing, and a cross-disciplinary profile that remains rare and in high demand. You will be supervised by Dr
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) Application Deadline 1 Nov 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position: Decision-Making for Heat Transition Planning under Data Sharing Constraints Can
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) Application Deadline 1 Oct 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not
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- 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 36.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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. The project brings together expertise in energy informatics, software engineering, data science, governance and social sciences to develop trusted data-sharing solutions for the heat transition. Within