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cutting-edge research infrastructure, close supervision by Prof. Spits and Prof. Olsen, plus access to a broad international network of collaborators, a dynamic, supportive, and family-friendly lab culture
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in AI: Generative Diffusion & 3D/4D Scene Synthesis: Re-design diffusion and NeRF-style models so multiple agents jointly reconstruct a scene. Semantic-Aware Compression & Network Information Theory
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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12 months, which - after a positive evaluation, will be extended to a total maximum of 48 months. Your contract will start on 01/11/25 at the earliest. The fellowship amount is 100% of the net salary
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to UGent software, shared documents and printers. Travelling costs from home to work will not be refunded for exchange PhD-students. Whether you are entitled to be reimbursed for work related travel depends
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operational employment. This doctoral research will thus leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modelling systems as graphs
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computing needs, and enabling rapid responses to potential issues in remote locations. The aim is to develop robust and scalable software solutions suitable for practical industrial deployment on a large
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the performance and explainability of Artificial Neural Networks (ANNs). In collaboration with our medical project partners, we hope to leverage the results of this ANN-based study to better understand social
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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or electrical engineering. You are motivated, creative and have a passion for academic research. You have an affinity with both experimental research and simulation software. You have a strong technical knowledge