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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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energy-efficient and sustainable transport systems through world-class research in tribology and machine elements. Friction losses in vehicle systems still account for a significant portion of global
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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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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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to be part of designing next generation mobile communications system? Please consider to apply for our open Postdoc position in 6G radio digital twin (RDT)-assisted situation-aware integrated sensing and
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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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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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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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Qualifications The following qualifications and experience will be considered an advantage: Experience with crop modeling. Experience with plant breeding. Background in data science, machine learning, and
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tasks include: AI support in the process chain: developing and applying image analysis, data process analysis, and sensor technology for textile production; using machine learning for process optimisation