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                Employer- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); Delft
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- Eindhoven University of Technology (TU/e)
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- Delft University of Technology (TU Delft); 3 Oct ’25 published
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- Erasmus MC (University Medical Center Rotterdam); yesterday published
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- University Medical Centre Groningen (UMCG)
- University Medical Centre Groningen (UMCG); today published
- University of Amsterdam (UvA); 26 Sep ’25 published
- University of Amsterdam (UvA); yesterday published
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- Utrecht University; 3 Oct ’25 published
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                Field
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                infrastructure managers in developing cross-sectoral strategies to proactively shape infrastructure demand, as an alternative to the traditional and increasingly untenable 'predict-and-provide' paradigm. By 
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                for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual 
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                our research team in the field of mixed-signal IC design, focusing on the implementation of sense to compute paradigm. The ideal candidate will have a strong background in circuit design and experience 
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                8 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Computer hardware Computer science » Digital systems Engineering 
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                new paradigm that aims to create a farming sector with positive externalities. By creating farming systems in balance with local soil, landscapes and communities, regenerative agriculture can restore 
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                , Biomedical Sciences, Molecular Sciences, Nanobiology). Experience with the basal transcription process, DNA damage response or with live cell imaging and microscopic data analysis is an advantage but not 
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                ., gravity field, magnetic field, seismic measurements). These measurements are often sensitive to various interior properties and when taken separately provide only a partial picture of the interior. Still 
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                separately provide only a partial picture of the interior. Still, this is often how the problem is approached. In this project, we aim to build a framework to perform a joint inversion of interior parameters 
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                images based on pseudo-haptics. The goals are to understand the interaction between exploration movement, multisensorial cues, and material properties and to enhance material experience and object handling 
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                these into interactive images based on pseudo-haptics. The goals are to understand the interaction between exploration movement, multisensorial cues, and material properties and to enhance material experience and object