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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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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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(or equivalent) in Computer Science, Artificial Intelligence, Engineering or a closely related field; Solid background in machine learning and/or evolutionary optimisation; strong programming skills (Python/C
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interest in neuro-behavioral sciences and a passion for behavioral signals. Demonstrable experience in advanced data analysis and data collection. Familiarity with machine learning and proficiency in Python
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networks, or network science, and relevant background knowledge n methods in machine learning and AI. The successful candidate will focus on innovating the field of network analysis with AI methods. Examples