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- Delft University of Technology (TU Delft)
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- Delft University of Technology (TU Delft); Delft
- Delft University of Technology (TU Delft); yesterday published
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- Eindhoven University of Technology (TU/e); Eindhoven
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- Delft University of Technology (TU Delft); Published 11 Nov ’25
- Eindhoven University of Technology (TU/e); today published
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image processing and analysis method development. The position builds on the lab's track-record in the field of computational imaging techniques for super-resolution microscopy and image analysis
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-Nederlanden and based at the Faculty of Economics and Business at the University of Amsterdam. The focus of our research is on developments in survival rates and life expectancy, how these developments
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across diverse scenarios, we aim to develop innovative algorithms that dynamically balance the improvement of speech intelligibility, sound localization, and environmental awareness, dependent
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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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project from the Dutch Polymer Institute (DPI). The main objective is to develop and validate a real-time, AI-enabled multi-sensor fusion platform for diagnostics and prognostics of polymeric bearing cages
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deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement
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, heavily relying on clinician expertise. This project funded by the Hanarth fund combines ultrasound imaging with histopathology data to train advanced AI models for automatic tumor segmentation, enabling
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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
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interpretation is subjective, heavily relying on clinician expertise. This project funded by the Hanarth fund combines ultrasound imaging with histopathology data to train advanced AI models for automatic tumor
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navigation. Develop control and guidance systems for precision landings on moving platforms. Create algorithms to decode optical communication signals. Conduct real-world test flights to validate system