234 machine-learning-"https:" "https:" "https:" "UCL" "UCL" PhD positions in Netherlands
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Mathematics (Inverse Problems), Computer Science (Machine learning, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of the NXTGen High-tech
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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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). 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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PhD candidate on Interprofessional Learning and Team Resilience through the Electronic Health Record
13 Mar 2026 Job Information Organisation/Company Maastricht University (UM) Research Field Educational sciences » Education Educational sciences » Learning studies Researcher Profile First Stage
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Vacancies 2x PhD positions in the Mathematical Foundations of Machine Learning on Graphs and Networks Key takeaways The Discrete Mathematics and Mathematical Programming (DMMP) group
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16 Jan 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Computer architecture Computer science » Computer hardware Researcher
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, silicon-proven AI/ML accelerator for transmitter error correction (digital predistortion/calibration). Your work will sit at the intersection of machine learning, DSP, and digital IC design, and you will
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Website https://www.academictransfer.com/en/jobs/358703/phd-in-scalable-safe-ai-for-sem… Requirements Specific Requirements A master’s degree AI, Machine Learning, Data Science, Computer Science or a
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socially relevant field at the intersection of education, technology, and learning sciences, while generating both scientific knowledge and practical guidance for schools. Where to apply Website https
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applicants should have a strong academic record with a solid background in Machine Learning. Knowledge of Vision-Language-Action models and Novel View Synthesis techniques is a strong plus. Good programming