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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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Employment 1.0 FTE Gross monthly salary € 3,706 - € 5,760 Required background PhD Organizational unit Faculty of Science Application deadline 14 October 2026 Apply now Join an ambitious
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sediment management. This will be done for two case studies, namely Western Scheldt and Wadden Sea. To facilitate knowledge exchange and the learning process, interactive workshops will be organized
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requirements For this postdoctoral role, we are looking for someone with a demonstrated background in SAR processing, SAR applications in agriculture and machine learning: A PhD in Earth Observation, Geodesy
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responses are pedagogically valid, contextually appropriate, and consistent with collaborative learning theory. Scaffolding mechanism design. In close collaboration with the PhD candidate and educational
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structure modeling in cancer immunotherapy design. Profile A — AI PhD in machine learning, computer science, computational science, or a related field. Strong experience with deep learning (e.g., PyTorch
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learned from ESA research and development activities relating to Zero Debris and consultation with ESA domain experts to identify challenges, constraints and opportunities associated with developing space
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translational microbiome researchers at Amsterdam UMC; present research findings at scientific conferences and publish results in peer-reviewed journals. What we ask of you You have/are a degree (PhD, or
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an inclusive, collaborative research culture. What we ask of you You are a curious and rigorous researcher who enjoys learning across disciplines. You can translate an ambitious methodological idea into a
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As a postdoctoral researcher, your primary responsibilities will be: Develop machine learning and deep learning models, with a strong focus on computer vision, for the characterisation and