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of flying birds to predict collision risk. This model will be fed by existing empirical data on bird flight behavioural responses to wind turbines from various bird radar studies. This model will allow
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in predictions derived from medical reports, and on integrating these uncertainties into downstream probabilistic time-to-event models. Applications will focus on prostate cancer, using large-scale
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an aerodynamic bird collision avoidance model, combining computational fluid dynamics (CFD) of the flow around wind turbines with the aerodynamic characteristics of flying birds to predict collision risk. This
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, inverse design methods, and physics-based modelling. The role is embedded within the ARC E2Crop Hub and the Centre for Atomaterials and Nanomanufacturing (RMIT University), which focus on renewable energy
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quality, particularly in controlled environments such as greenhouses and vertical farms. By integrating plant physiology, modelling, and data-driven approaches, the group aims to predict plant performance
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predictive reliability of advanced power electronic modules and systems. Location will be in Delft, as a team member of ECTM, in close collabrations with NL and EU industrial partners. Job requirements MSc
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, MES, APC). In-depth research in areas such as Reinforcement Learning, Large Language Models, Digital Twins, Predictive Maintenance. Overseas research experience or experience collaborating with industry
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digital process-monitoring and predictive modelling approaches for intelligent and reliable micro-EDM manufacturing. The project includes potential international secondments at Sarix SA (Switzerland
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funded, international doctoral position within the Marie Sklodowska-Curie Doctoral Networks (MSCA-DN) project MicroMan4Health (Website: https://www.microman4health.eu/ ). (Data-Centric MicroManufacturing
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position This PhD project is connected to FME NorthWind (https