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Horizon Europe – MSCA-DN, tackles challenges in designing, optimizing, selecting materials, and manufacturing small-scale turbomachinery for applications in heat pumps, fuel cells, organic Rankine cycles
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. This intervention constitutes optimal timing and a comprehensive design to achieve its intended goals, i.e., improved functional recovery post-TJA and general health, and decreased socio-economic burden
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primarily on the development, validation, and implementation of the Psychological Referral Optimization algorithm (PRO). PRO is a brief digital e-screening tool designed to support early identification, risk
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combining particle damping with architected metamaterial concepts enabled by Laser Powder Bed Fusion (LPBF). The proposed approach will employ optimized internal cavities acting as Tuned Mass Dampers (TMDs
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of the principal investigators, the candidate will work closely with the other project members, including the doctoral researcher responsible for the Greek and Latin textual sources and the postdoctoral researcher
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learning, with the aim of controlling the vessel in an optimal and efficient manner. In this context, control is formulated as a trade-off between different objectives, such as minimising energy consumption
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broad genomic screening and; Support hospitals in mitigating the impact of pandemics through optimized decision-making and data collection strategies. The project brings together experts in artificial
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algorithms. model and optimize end-to-end physical-layer performance, hardware non-idealities, and overall power consumption. focus primarily on space and security topics (satellite communications, reliable
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will be provided by a postdoctoral researcher working on the project. As a researcher, you will be supported by the project team, including the principal investigators Prof. Dr. Katelijn Vandorpe and
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with advanced control methods. The research will therefore explore RL algorithms that not only operate optimally against such competing objectives but also effectively under uncertainty, changing