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, this position, is on wireless propagation studies, data collection and implementation of machine learning, while the LiU focus is on new models and methods for machine learning. More about the project (elliit.se
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, C++ or similar languages. Good knowledge of network communication and integration between different systems, such as robots, AI and digital twins. Good knowledge and experience of machine learning
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learning, large language models, or other generative AI systems. Experience with the design, implementation, deployment, optimization, or evaluation of AI/ML systems, or resource-constrained environments
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consists of method development, in which existing simulation techniques are further developed using machine learning algorithms to enable more efficient, scalable, and realistic simulations and material
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models for intelligent environments. The primary area of research involves developing AI models that can learn to represent real-world phenomena based on various types of observations, including video
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, drawing on machine learning where it strengthens these methods. The research supports mission-critical scenarios and feeds into an end-to-end resilience proof of concept developed together with Swedish and
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, knowledge-driven models and AI-based decision support can be integrated to support resilient and energy-aware manufacturing systems. Special emphasis will be placed on multi-objective optimization, learning
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a doctoral student with a strong background in machine learning, mathematics, and modeling, and an interest in biological systems. The successful candidate will join a project to understand and model
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School