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Field
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Electron Laser (EuXFEL) is an X-ray laser facility driven by a superconducting linear accelerator. It is currently the brightest X-ray source of its kind, enabling unprecedented discoveries in the physical
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development of ICON model as needed for your work Disseminate your research through high-quality peer-reviewed publications and presentations at conferences Teach independently within the scope
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activities . You can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
knowledge of AI-enhanced planning in shipbuilding supply chains. Apply quantitative methodologies, such as simulation, analytical modelling, and AI‑driven techniques, to develop decision support for efficient
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future tasks: Active participation in research and teaching, which means: Lead independent research on your doctoral thesis topic Contribute to the further development of ICON model as needed for your work
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collective cell migration. A central goal of the project is to develop and apply data-driven theoretical frameworks that infer interaction rules directly from multicellular migration experiments. We therefore
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employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working
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development of ICON model as needed for your work Disseminate your research through high-quality peer-reviewed publications and presentations at conferences Teach independently within the scope
-
research projects at the intersection of infectious disease modelling, Bayesian inference, AI, and public health. Projects span AI-driven epidemic forecasting, transmission modelling in the ASEAN region
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Fully Funded PhD Studentship (Home Fees) Project Title: Developing Fair and Robust Cancer Risk Prediction Models Using Health Data Supervisor: Professor Angela Wood (Professor of Biostatistics and