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to science, engineering and society. You will focus on optimization-based, data-driven and partially model-based control methods. You will have access to a strong research network and a broad range of
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Infrastructure? No Offer Description Start date/duration as soon as possible until 14.09.2027 Job profile: Your responsibilities: PhD thesis in the field of software engineering and model-driven engineering
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, visiting researchers, master's students, etc.) Research Context Recent advances in mobile robotics have been driven by remarkable progress in perception, deep learning, and control. However, current robotic
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noisy, partially mediated observations. These models will incorporate biologically informed structure, including protein-protein interaction networks derived from data-driven sources such as protein
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models and monitoring data to assess its current structural state and predict its remaining lifetime. This will enable the condition of welded structures to be monitored throughout their service life
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application! We are looking for a PhD student in Medical Science, AI and Bioinformatics. Your work assignments This project aims to develop AI foundation models for integrative single-cell and multi-omics
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characterisation, and computational modelling to investigate the relationship between matrix properties and osteogenesis. This will contribute to deciphering the importance of mechanical stimulation of the cellular
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developing the first observation-driven, AI-ready global river data infrastructure. Reporting to Professor Louise Slater, you will lead research combining large-scale Earth observation data, global hydrography
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software developers to integrate data‑driven models with mechanistic or physics‑based models and domain expertise; showing thought leadership on applying data & AI-solutions in the food & biobased domain
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. The project will bridge wind farm aerodynamics, advanced control, system identification, filtering, and data-driven modelling, with a strong emphasis on combining physical knowledge with measurements rather