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Department: Chemistry Title: Combinatorial Discovery of Peptide Materials as Ice Binding Protein Mimics Application deadline: All year round Research theme: Chemical Biology, Materials Chemistry
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tumours and metastases with the goal to design combinatorial therapeutic approaches. The project will involve the use of genetically complex organoid-derived transplantation mouse models of pancreatic
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effective energy management system (EMS) is then necessary to monitor the states and optimize the use of HESS, consequently enhancing the eVTOL’s desired performance. The state-of-the-art review indicates
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of challenging proteins. Moreover, you will determine whether the success of such alternations depends on protein family and on mRNA characteristics such as codon optimality. You will construct a panel
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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(HTPB) and isocyanates for optimization of formulation (pot life) and product mechanical properties for application in solid rocket propellants. Due to the confidential and commercially sensitive nature
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; implementation of digital twins that enable real-time decision optimization; and establishment of cross-industry frameworks that allow technology transfer between sectors. Your findings will be published in high
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems