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- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e)
- Delft University of Technology (TU Delft); Delft
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- Delft University of Technology (TU Delft); 3 Oct ’25 published
- Elestor BV
- Erasmus MC (University Medical Center Rotterdam)
- Erasmus MC (University Medical Center Rotterdam); Rotterdam
- Maastricht University (UM); Maastricht
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representations. In this project, you will substantially improve quantitative magnetic resonance imaging (MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers
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of machine learning to evaluate the predictive value of biomarkers from various sources: donor-related data, perfusion fluid, and kidney biopsies. Kidney biopsies may contain unique information about organ
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team of experienced researchers in imaging, machine learning, oncology, and pathology. We do not discriminate on the basis of sex, gender, belief, culture, place of birth or occupational impairment when
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protocols, ITC will focus on the monitoring and response parts, building on many earlier projects revolving around the use of UAV/drones, computer vision and machine learning, change and damage detection, and
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. Nice to have: Practical experience with machine-learning frameworks (e.g., PyTorch). Prior tape-out experience (ASIC or a complex FPGA prototype) and familiarity with the digital back-end flow (synthesis
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you have a background in deep learning and computer vision? Are you
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& Image Sense lab (VIS lab), at the University of Amsterdam. VIS lab is a world-leading lab on Computer Vision and Machine Learning, and has over 30 PhD students, postdoctoral researchers and faculty
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on the monitoring and response parts, building on many earlier projects revolving around the use of UAV/drones, computer vision and machine learning, change and damage detection, and multi-data integration, such as
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intersection of mechanics, materials, and machine learning. Collaboration with international experts from diverse disciplines. Access to cutting-edge computational and experimental facilities. Supervision of MSc
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, you will combine continuum mechanics, machine learning, experimental imaging, and mechanical testing to design and characterize self-sensing soft matter capable of revealing its mechanics from