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project seeks to turn a problem into an opportunity, by developing digital tools and Life Cycle Assessment (LCA) models to (1) minimize waste and (2) accelerate circularity and sustainable resource use in
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of Tartu) PhD task description This PhD project aims to develop, model, and evaluate innovative Smart City solutions for energy balance and efficiency. Such solutions can be integrated into the urban-scale
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nanofibrous layers, including composite multilayer membranes. Currently, there are 1) no readily available nanofiber quality models for multilayer membranes, and 2) no robust and scalable methods for model
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(BME). Electrospinning is a flexible, scalable and affordable method to deposit nanofibrous layers, including composite multilayer membranes. Currently, there are 1) no readily available nanofiber
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necessary to consider also the control methods through which it is possible to increase both machine efficiency and controller efficiency. The overall goal of the project is to develop the control methodology
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of Ni#Al intermetallic-based superalloys. The project will focus on predicting thermal histories, residual stress development, and crack susceptibility during additive manufacturing. Using finite element
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Description The aim of this research is to enhance the durability and fire resistance of veneer-based wood products by developing and optimizing a sustainable wood densification process. The study seeks
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pipelines on iseAuto. Research and develop LLM-driven scenario generation tailored to stress E2E models. Design metrics for scenario quality, coverage, and system robustness. Integrate validation workflows
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and responsibilities of the service providers. By doing so, it aims to develop actionable guidelines that help organizations ethically implement AI while delivering meaningful value to individuals
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optimization, and the interplay between microstructure properties and the LPBF technique. Key aspects of the project will include the: (1) Development of novel and next generation functional materials for LPBF