15 structural-optimization PhD positions at Technical University of Denmark in Denmark
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challenges. This PhD project aims to advance the efficient, controllable, and optimized use of renewable energy by integration of advanced TES technologies (latent heat and thermochemical storage) in
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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
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process. Together, these innovations aim to make column generation more practical for solving real-world, large-scale optimization problems. These innovations will be tested within a structured software
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and kinetic modelling Expression, purification, and characterization of enzymes from fungal and bacterial sources Development and optimization of enzyme assays Structure–function studies of enzymes
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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competences within computational modelling, optimization and integration of thermal energy storage technologies – such as large water pits and phase change material storage. You will work with colleagues, and
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the interfacial phenomena between water contaminants and adsorbent materials. As a member of the “Nano-Micro-Macro. Structure in Materials” research group, led by Prof. Joerg Jinschek, you will push the boundaries
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the optimization of bioactive compound extraction from various seaweeds for the development of fortified foods. This PhD position aims to (i ) identify suitable seaweed species for high-yield protein extraction, (ii
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group is a highly ambitious group, pursuing research on microfabrication of 3D polymer and carbon structures and devices and their application in biomedical applications, bioelectrochemistry and
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the collaboration. In particular, the following open questions will be addressed: What is a sequence-structure-function representation space for molecules in the context of closed-loop optimization, that supports