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explainable AI for large-scale and complex datasets by developing algorithms, pipelines, and tools suitable for critical decision-making contexts. The doctoral student will be based at the Health Technology
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or more of the following areas: cybersecurity, network security, intrusion detection systems, software security, or critical infrastructure protection (e.g. SmartGrids). Good knowledge in one or more of the
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knowledge in one or more of the following areas: cybersecurity, network security, intrusion detection systems, software security, or critical infrastructure protection (e.g. SmartGrids). Good knowledge in one
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engineering or a related field. Documented experience in industry-related research and collaboration with business and industry. Documented experience in simulation of complex systems-of-systems in a product
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demands are significant challenges of today’s AI systems. One promising alternative is spiking neural networks (SNNs) executed on neuromorphic hardware. Neuromorphic computing tries to mimic how the brain
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and industry. Documented experience in simulation of complex systems-of-systems in a product development context. Documented experience in value-driven product development. Strong ability to communicate
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by real-world challenges arising across different application domains. The research focuses on strengthening product/production development processes, and decision-making in complex engineering systems