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- Delft University of Technology (TU Delft); 17 Oct ’25 published
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- University Medical Center Utrecht (UMC Utrecht); Published 31 Oct ’25
- University Medical Center Utrecht (UMC Utrecht); yesterday published
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- University Medical Centre Groningen (UMCG); Groningen
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- University of Twente (UT); today published
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Field
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, tools, or artistic creations, humans instinctively explore the unknown in order to acquire information about it, to make sense of it, to act on it, and to appreciate what is in front of them
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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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-ACCENT project aims to fill this gap by combining insights from cognitive psychology, neuroscience, AI engineering, human-computer interaction and social science, with lifespan perspectives. Using advanced
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such as case weighting, anomaly detection, and model-based prediction (e.g., geostatistics and machine learning), using auxiliary geospatial or remotely sensed data. Quantifying uncertainty and correcting
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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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, development of data (pre-)processing pipelines, and machine learning model training to identify relevant biological states of the liver (e.g., healthy, recovering, not healthy). The (soft) sensor development
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Christmas and 1 January; multiple courses to follow from our Teaching and Learning Centre; a complete educational program for PhD students; multiple courses on topics such as time management, handling stress
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master’s degree in electrical engineering, computer Engineering, or a related field. Strong background in mixed-signal circuit design and simulation. Familiarity with IC design tools and tapeout flow and
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between Christmas and 1 January; multiple courses to follow from our Teaching and Learning Centre; a complete educational program for PhD students; multiple courses on topics such as time management
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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data