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computational approaches that integrate process-induced stresses into the structural design stage. Project goals The objective of this PhD project is to develop a topology optimization framework for LPBF
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to renewable energy sources. Thermodynamic cycles (power generation cycles, refrigeration cycles, heat pumps) play a central role in this transformation, but their optimal design remains a complex scientific
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construction of complex metallic components. Activities include planar and non-planar slicing, toolpath optimization, robotic integration, and experimental validation on aluminum alloys and structural steels
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Certifications/Licenses Required Knowledge, Skills, and Abilities Experience with AI-driven model updating and calibration of structural systems, including learning-based or optimization approaches Strong
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application of PowerMarketSim, an open-source electricity market simulation framework, to assess the profitability and system value of flexible assets under evolving market conditions. The work is structured
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, Infected macrophage populations. Perform parameter estimation using optimization and machine learning approaches Develop numerical schemes for high-dimensional structured PDEs (pseudospectral methods
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of finite element modelling strategies (beam and continuum formulations) for the structural characterization of continuous fiber-reinforced additively manufactured prosthetic feet, with specific reference
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the first stage, we will thoroughly investigate the structure and quantum control capabilities of the proposed strongly polar molecules. Next, we will develop an optimal method for encoding qubit states on
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with industrial research partners, develop innovations, and offer students excellent academic teaching in the fields systems theory, automation, and control engineering. More info at https
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hierarchical and composite nanofiber systems with prescribed structures to optimize performance in targeted applications while expanding the fundamental understanding of nanofiber fabrication processes and their