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on the modelling and optimisation of PRO systems using advanced Computational Fluid Dynamics (CFD) and Machine Learning (ML) techniques. This role offers an exciting opportunity to contribute to cutting-edge
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with statistical and numerical analysis methods as applicable to strain design problems is a distinct advantage. Familiarity with machine learning tools such as PyTorch, HuggingFace transformers and
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. theses at the interface between structural engineering and machine learning. You will disseminate your research through peer-review publications and participation in international conferences. You will
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thermomechanical process simulations such as casting and welding. The research activities at SDU-ME spans widely from fluid mechanics, condition monitoring, machine learning, fatigue, maritime structures
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expected to provide outstanding education, supervise bachelor, master and PhD level students. Candidates for this position must have a solid education that enables them to teach within (at least one
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project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer engineering
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. theses at the interface between structural engineering and machine learning. You will disseminate your research through peer-review publications and participation in international conferences. You will
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in ion transport and (2) using machine learning methods to design protein binders. The incoming postdoc will have the opportunity to mould the project to a significant degree. The candidate should have