88 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Netherlands
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Internet Exchange (AMS-IX), and the Faculty of Science of the University of Amsterdam. About Research group The CWI Machine Learning research group focuses on how computer programs can learn from and
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assessment. You will be provided with access to various engineering and computation toolsets along with the high-performance computer. A good background in numerical methods and computational platforms is
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Employment 0.8 - 1.0 FTE Gross monthly salary € 4,537 - € 6,209 Required background PhD Organizational unit Faculty of Philosophy, Theology and Religious Studies Application deadline 10 August 2025
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(UQ) for machine learning and its validation. Your areas of research will be chosen based on both your own expert judgement and insight into trends and developments and on team requirements to ensure
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with a PhD in Human-Computer Interaction, Remote Sensing, Geo-Information Science, Cognitive Science, or a closely related field. The ideal applicant possesses a strong technical foundation, as
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, Linguistics and Media and Journalism Studies. For this role, we are looking for someone who: Has a PhD degree in any area related to the tasks (e.g. Computer Science, Digital Humanities, or Information
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records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records
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applications* in close collaboration with other discipline experts (software, microelectronics and applications engineers). * except for RF payloads. ** including artificial intelligence and machine learning
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towards a future-proof logistics system with a special focus on machine learning-based collaborative scheduling, resource sharing, and self-organisation. The EngD position corresponds to a 2-year post
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any