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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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processing, machine learning, computational imaging, and clinical translation. Beyond your individual research contributions, you will serve as a technical coach for the PhD researchers, helping to align
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(adaptive) imaging strategies and reconstruction. The research combines ultrasound physics, signal processing, machine learning, computational imaging, and clinical translation. Beyond your individual
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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
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: Within this international project, TU Delft will develop a machine learning-based forward operator to enable the assimilation of SAR imagery into the crop growth model. You will: Process SAR imagery over
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Specific Requirements The ideal candidate has the following qualifications: - interest in human cognition - experience with neural data, especially EEG or MEG - experience with machine learning models
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; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python, JavaScript, PostgreSQL) with clear expertise in front-end and
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, with a strong interest in the integration of geospatial Artificial Intelligence (AI) and machine learning. Are you enthusiastic about the chance to combine research in Remote Sensing and AI with teaching
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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and authorities interested in improving civic participation. The research in this postdoctoral position focuses on text and image feature learning for news ecosystems, analysing the complex