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Field
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26 Oct 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Informatics Computer science » Programming Mathematics » Algorithms
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) Interpretable machine learning for network adaptation. In this thesis, the student will study how interpretable models and explainable learning algorithms could be used in real cellular networks for safe
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) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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Framework Programme? European Union / Next Generation EU Reference Number 165526 Is the Job related to staff position within a Research Infrastructure? No Offer Description Analysis and design of algorithms
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in basic control-flow analysis. Process mining, as it stands today, is primarily based on computational techniques and algorithms to analyze and optimize processes. Methods such as process discovery
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. About your role: Develop improved physical models of the image formation process in holographic X-ray imaging Design and implement reconstruction algorithms for handling large-scale tomographic data from
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of federated algorithms that enable fair management of the advantages and duties of energy communities in which vulnerable people live. The automatic generation of data models using AI technology will enable
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qualifications will be considered. Experience of using machine learning algorithms and toolsets, ideally in a research context. Strong programming skills (e.g., Python, Java, C++) An interest in physiological
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implementation of security provisioning algorithm in DFL environment Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » Communication