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applications from individuals with experience in: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques
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. Exploring how these models can enhance human-computer interaction and improve our understanding of multimodal communication.To do so, you will have full access to motion-capture and virtual-reality labs, 3D
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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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: 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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Postdoc: Geospatial AI Modelling & Uncertainty Quantification of Carbon Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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23 Aug 2025 Job Information Organisation/Company University of Twente (UT) Research Field Computer science » Programming Researcher Profile Recognised Researcher (R2) Country Netherlands Application
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Postdoc: Hybrid Geospatial Modelling and Scenario Development of Carbon Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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select a technique adaptable in the laboratory scale environment for further experimental work. Design and perform lab-scale experiments in the laboratories at TU Delft. Develop a mathematical model
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cutting-edge multimodal deep learning models that integrate imaging and clinical data to personalize treatment and follow-up strategies. In the Netherlands, around 75% of patients with an abdominal aortic
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availability of data and connectivity through the Internet of Things create new opportunities to incorporate real-time insights into decision-making, combining tractable modelling with provably efficient