30 condition-monitoring-machine-learning PhD positions at Leiden University in Netherlands
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Candidate Human-Centered Interpretable Machine Learning (1.0fte) Project description In recent years, practitioners and researchers have realized that predictions made by machine learning models should be
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Apply now The Faculty of Science, Leiden Institute of Advanced Computer Science,is looking for a: PhD Candidate Human-Centered Interpretable Machine Learning (1.0fte) Project description In recent
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://www.universiteitleiden.nl/en/science/mathematics . What you bring The successful candidate is expected to have: A master in statistics, (applied) mathematics, machine learning or a closely-related quantitive discipline (to
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enhance real-time decision-making in road traffic management. The project aims to bridge the gap between recent advances in AI and machine learning, in particular, multimodal and instruction-tuned
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. The research will combine computational modeling (e.g., NLP, machine learning, deep learning) with human-centered research (e.g., user studies, experimental design, qualitative analysis). We are looking not only
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emotion safety is crucial; Design interventions to reduce bias and improve fairness and safety in human-AI interaction. The research will combine computational modeling (e.g., NLP, machine learning, deep
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, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong programming skills (Python/C++); Proven interest in generative models
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degree in Computer Science, Artificial Intelligence, Data Science, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong
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First Stage Researcher (R1) Country Netherlands Application Deadline 14 Nov 2025 - 22:59 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU
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26 Sep 2025 Job Information Organisation/Company Leiden University Research Field Computer science » Computer hardware Computer science » Digital systems Researcher Profile First Stage Researcher