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Centrum Wiskunde & Informatica (CWI) has a vacancy for a 4-year PhD position (m/f/x) on the subject of Reliable AI-powered Data Analysis in collaboration with the University of Amsterdam. Interested
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, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform statistical analyses to assess stability and plasticity of multisensory
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processing, or optimisation to turn heterogeneous knowledge (channel/network state, maps and topology, mobility, hardware constraints, and task-level KPIs) into reliable and efficient decisions. The work spans
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-consuming and inefficient. This project aims to develop a faster, AI-powered method using Hyperspectral Imaging (HSI) to enable reliable, scalable microplastic quantification in real-world agricultural
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visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
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science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in Python Independent and analytical way of working Reliable and thorough
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reasoning domains. This work will blend cutting-edge experimentation - spanning RL, few-shot learning, meta-learning, etc. - with formal analysis to push the boundaries of what modern AI systems can reliably
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to increase data and software interoperability, enabling the automated reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable
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stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex
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the models, ensuring usability, reliability, and integration into operational workflows. The successful candidate will benefit from interdisciplinary training in experimental design, advanced speech analysis