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fundamental AI methods together with their software implementations for interpretable statistical fault prediction and lifetime assessment in the context of Structural Health Monitoring of operating wind
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Python and/or Matlab. Experience with software-defined communication systems, emulation tools, and machine learning techniques is considered an advantage. Most importantly, you are eager to learn and apply
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intelligence, and research software engineering, and is interested in developing robust, transparent, and sustainable computational tools. Experience with first-principles electronic structure methods, machine
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Experience with firm level econometric analyses or with processing of large firm level datasets will be an advantage, but it is more important that you have experience with software tools such as Stata, SAS, R
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familiar with quantitative statistical analysis and has at least a basic understanding of statistical analysis framework or software. If you do not have any experience with the above but are interested in
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At the Technical Faculty of IT and Design, Department of Sustainability and Planning, a PhD stipend is available within the general study program Development and Planning. The stipend is open for
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to research‑based teaching, employing innovative methods to enhance student learning. It oversees a graduate program in Population Studies. The center fosters an inspiring academic environment and strives
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-year employment is funded by the Energy Technology Development and Demonstration Programme (EUDP) and aims to deliver a standardised, robust, and scalable subsea electrode unit for HVDC systems. The PhD
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of Bayesian optimisation Experience of numerical computing for optimal control, dynamical systems, Bayesian inference and Bayesian optimisation. Experience of running controlled fermentation experiments
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Department of Energy at Aalborg University (AAU Energy) invites