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to develop new methods, for example using machine learning. have a proven track record of independent research funding and high quality publications. have at least 5 years of post-PhD work experience
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a national and international scale, yet small enough to offer a personal and engaging learning experience. In this way, we contribute every day to a safer and more sustainable world. Impact with law
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cases. We are particularly interested in how AI, Data Science, or Machine Learning techniques can be used to quantify and assess software and system security from open source software to cloud services
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sciences, law, and philosophy. Four WPs address citizen-empowerment-scenarios (CES) in healthcare, mobility, public governance, and healthy living. Each PhD position is embedded in one work package and
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on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing
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and machine-learning-driven analyses create opportunities for high-frequency, minimally invasive measurements. Proof of concept will be used in sheep, cattle or pigs, initially based on data from
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16 Jan 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Educational sciences » Education Educational sciences » Learning studies Engineering
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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. Methodological Approach Candidates will develop and apply state-of-the-art machine learning techniques, including deep learning, representation learning, variational autoencoders, and graph-based models. A strong
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models that provide evidence-based reasoning for mission-critical decisions. Explainable AI for mission-critical decision support: design interpretable machine learning architectures capable of offering