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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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learning Deep learning model generalisation techniques Translating deep learning models into clinical settings Experience developing deep learning models for real-time image/video segmentation, object
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? No Offer Description Will you develop our next generation environmental impact assessment to make PV circular and more sustainable? Are you an expert in LCA modelling, and you want to make the energy
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the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and healthy tissues using both
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Power Electronics (EPE) Group at the Department of Electrical Engineering. Information Power electronics converters are systems that process electric power in various applications, including renewable
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delineation and improve the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and
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to localize anomalous sounds, related to faults, in a complex acoustic environment, characterized by moving sound sources and reverberations. Purely relying on physical models describing the acoustics
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, aiming to transform the care for patients with abdominal aortic aneurysms (AAA). You will develop and validate cutting-edge multimodal deep learning models that integrate imaging and clinical data
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through the Internet of Things create new opportunities to incorporate real-time insights into decision-making, combining tractable modelling with provably efficient solution methods. As a postdoctoral
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motivated individual with the following competencies and skills: Proficiency in electrical design, multi-model sensor technology, and experimental analysis. Strong communication skills and a genuine interest