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- University of Amsterdam (UvA); Published today
- Delft University of Technology (TU Delft); Delft
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- Max Planck Institute for Psycholinguistics; today published
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- University of Amsterdam (UvA); Published 7 Nov ’25
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biomedical image processing. Within the scope of machine learning and computer vision, there will be freedom to suggest your own research directions, and to become acquainted with new techniques and approaches
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to your expertise. What do we require? A PhD degree (or equivalent qualification) in AI (e.g., machine learning, natural language processing or computer vision); A strong scientific track record, documented
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methods, integrating qualitative approaches (e.g., interviews, walk-alongs, focus groups) with quantitative techniques (e.g., computer vision, physiological sensing, environmental monitoring, crowd
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) with quantitative techniques (e.g., computer vision, physiological sensing, environmental monitoring, crowd behaviour analysis), as well as researching existing sources of knowledge in the literature and
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qualification) in AI (e.g., machine learning, natural language processing or computer vision); A strong scientific track record, documented by publications at first-tier conferences and journals (e.g., NeurIPS
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competencies Education You should have completed within the past five years or be close to completing a PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science
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strong background in machine learning, computer vision, or data-driven modeling. You have extensive experience in the development and implementation of AI and machine learning algorithms, ideally with
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rich theoretical and computational environment supported by the Multimodal Language Department. Requirements Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP
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PhD in biology, cognitive science, or an adjacent field (e.g. biomedicine, computer sciences); A strong academic track record, including high-quality publications (quantity is less important
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(completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative modelling (diffusion