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to the cyclotron motion of electrons near the plasma center. However, recent models predict that as these waves traverse the plasma edge, they may be influenced by non-linear plasma–wave interactions. Some studies
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optimal control, robust control, distributed control, and model predictive control. A background in power system analysis, dynamics, control and/or converter control is considered a strong advantage
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-pathogen interaction assays; Biofilm models; Proteomics & LC-MS/MS. DC12: Optimizing bioreceptor function in interaction with graphene. Based on modelling/prediction of interaction of receptor molecules
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measurement techniques/ sensors. Experience with system modelling and simulation (e.g., TRNSYS, Python, or similar tools). System and control engineering (e.g. digital twins, model predictive control) –pre
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pathogenesis and host-pathogen interaction assays; Biofilm models; Proteomics & LC-MS/MS. DC12: Optimizing bioreceptor function in interaction with graphene. Based on modelling/prediction of interaction
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PhD scholarship in Corrosion Mechanisms of Power Semiconductor Device and Components - DTU Construct
, gases and applied potential conditions. The project will also include the development of advanced simulation models to characterize and predict moisture transport through gel substrate and interfacial
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microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM components are in use
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on the development of AI models for analysis of cardiac CT scans, with the aim to explore how machine learning models can quantify cardiovascular disease and predict future events from CT scans. The project will