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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
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
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- Eindhoven University of Technology (TU/e); today published
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- University of Amsterdam (UvA); today published
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Field
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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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of machine learning (ML) and quantum many-body physics. We are also happy to work with experts in one of the two fields who are committed to learning the other. Moreover, we look for interest in developing
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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
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computer vision algorithms for accurate landing navigation. Develop control and guidance systems for precision landings on moving platforms. Create algorithms to decode optical communication signals. Conduct
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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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applications in the media change journalism, the public sphere, civic engagement and economic competition. We will develop and test new AI-applications to help solve problems such as disinformation, algorithmic