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: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques Translating deep learning models into clinical
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learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques Translating deep learning models into clinical settings
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5 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Programming Researcher Profile Recognised Researcher (R2) Country
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perform a prospective trial at the Dutch Breast Cancer Screening Program to determine the impact on screening performance when optimizing the radiologist’s interpretation. This trial will involve two
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to and lead some of the above tasks. Job requirements To be eligible to apply, you should: Hold an PhD in geoinformatics/geomatics, computer sciences or engineering (or in a related discipline), ideally
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Livable Urban Spaces” under the EU Driving Urban Transitions (DUT2024) program. The project is led by Eindhoven University of Technology (TU/e), has consortium partners from Austria, France, Switzerland
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/video segmentation, object tracking, reinforcement learning. Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation
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to have the following skills and experience. We welcome applications from individuals with experience in: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep
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and courses. Partially paid parental leave Attention for working healthy and energetically with the vitality program. Will you need to relocate to the Netherlands for this job? TU Delft is committed
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Netherlands Application Deadline 30 Sep 2025 - 22:00 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 36.0 Is the job funded through the EU Research Framework Programme? Not funded by a