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programmability, network exposure APIs, service orchestration, O‑RAN, network slicing, and data-driven optimization. You have proven experience with AI/ML pipelines, including data processing, model training
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission
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contribute to innovative research projects aimed at unraveling cellular interactions and immune mechanisms in liver disease. The following responsibities (not limited) are expected: Develop, optimize, and
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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researcher in the context of a multidisciplinary project to classify materials in waste streams, including using X-rays. The goal is to optimally use the spectral capacities of a new generation of X-ray
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allocation and optimization Joint Communications and Sensing/PNT systems Network virtualization and network slicing MAC techniques/protocols for wireless systems Multi-antenna signal processing Graph signal
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, including the selection and application of scale-up modelling approaches (e.g. process simulation, expert interviews, and the integration of scale and learning effects) for the identified scenarios
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or MATLAB, integrating data preprocessing, feature extraction, and classification for hyperspectral and fluorescence lifetime datasets. Optimize algorithms for batch processing and scalability, enabling high
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the research team in the area of Swarm Intelligence, Reinforcement Learning and Optimization Techniques. As a Postdoctoral researcher, you will: Lead cutting edge research in Swarm Intelligence and Machine