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Dutch), cognitive modeling of human problem solving processes, mechanistic interpretability in AI-models, as well as extensive computer programming experience in R and Python. Given that the project lies
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Dovrolis: PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity. ICML 2025 Job requirements Master’s degree in: Computer Science, Machine Learning
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Electrical Engineering, Computer Science, or a related discipline. A research-oriented attitude. Solid background in machine learning and optimization methods. Knowledge and experience in (wireless
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degree in AI, Computing Science, Mathematics, or Data Science. Strong coding, communication and organizational skills. Demonstrable experience with using machine learning packages (e.g., PyTorch
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learning algorithms. Personalizing user interactions by building models that adapt explanations to specific knowledge levels and interests of users, so that user modelling and formal reasoning transform
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modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning). Experience in annotation software such as ELAN and PRAAT. Existing peer-reviewed journal publications and conference
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explainable AI (XAI) methods with user-centred interaction design, combine machine learning with alternative AI methodologies (e.g., rule-based reasoning, knowledge graphs, hybrid approaches where relevant
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, and how AI systems can remain responsive to contextual knowledge in real decision environments. Another possible avenue concerns theorising with data, focusing on how inductive machine learning
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storyClose this story Does this sound like you? You hold a Master’s degree in cognitive neuroscience or an adjacent field (psychology, biology, biomedical sciences, computer sciences, or any other relevant MSc
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experience and profile MSc in artificial intelligence, statistics, computer science or a related field; Strong background in machine learning and/or statistics; Preferred prior knowledge/experience with