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data and multimodal datasets combining imaging and molecular measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with
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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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at the interface of automatic control, electrochemistry, and machine learning. The position will also involve close collaboration with another postdoctoral researcher working on a complementary project in physics
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. The following experience will strengthen your application: industrial product development or manufacturing research modelling and simulation, digital twins or digital threads AI, machine learning
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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
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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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description Work on EU projects to develop next‑generation transport, emission and health forecasting models by integrating deep learning, xAI, and diverse data sources such as traffic sensors, smart‑card data
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visualization and scientific communication Extensive knowledge of relevant machine learning and AI techniques Exceptional collaborative abilities Self-motivated individual with ability to work independently
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aims to explore to which extent machine learning methods can help with these tasks, e.g. object reconstruction and signal/background discrimination. This will be a focus in the project. One exciting
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data analysis, such as signal processing, modeling, statistics, or machine learning Excellent written and verbal communication skills in English, particularly in a research context It is meriting to have