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qualifications around data-driven digital twins, energy systems modelling, forecasting and control. Some prior knowledge on distribution grids and methods for grid services is preferred. Moreover, the following
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model checking. You should be well versed in basic statistics and practical programming skills is a must. Knowledge about the inner workings of GenAI would be nice but not necessary. You must have a two
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generalization. However, existing machine learning theory does not fully explain this behavior, leading to the development of new approaches. A promising explanation is that models are implicitly regularized
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, laboratory testing and data augmentation. Your main goal will be to develop predictive models for assessing the degradability of bioplastics, facilitating a transition to more sustainable materials. More
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modelling, and prediction tools. Fouling Control Coatings Fouling Control is performed by specifically designed materials to remove or prevent biofouling from i.e. ship hulls, as bio fouling leads
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advanced materials. Experienced in both strain development and related modelling & data analysis. Experienced with processes of biomanufacturing, including fermentation, downstream processes and scale-up
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innovative services and products which benefit people and create value for society. DTU Health Techs expertise spans from imaging and biosensor techniques, across digital health and biological modelling
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collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class with
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primarily experimental, complemented by numerical modeling, and will be carried out within the “Fiber Optics, Devices, and Nonlinear Effects” group at DTU Electro. As a PhD student, you will be part of a
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engineering, operational research and energy systems modelling through dedicated courses and/or related work. The following further qualifications will be considered in the assessment: Strong background and