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groundbreaking research. The project is devoted to learning-based control for high-dimensional data. Application to individually optimized immunotherapy for cancer will also be considered. The grant covers two
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quality of life. This project aims to develop and validate a personalized, evidence-based cognitive training system through a multicenter Randomized Controlled Trial. The system focuses on enhancing
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. They should demonstrate hands-on experience in embedded programming (C/C++) for microcontrollers, as well as familiarity with automation tools (e.g., LabVIEW, PLC) and version control systems (e.g., Git
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technical team. You will work on the design, assembly, and optimization of experimental setups and inspection systems (femtosecond laser illumination, PMT detection), considering nonlinear optics and
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tools to tackle the voltage security problem in transmission networks with a large presence of renewable generation by optimally employing non-costly control actions like (i) displacement of available
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the CV and/or in the motivation letter. Additional optional skills and qualifications: Previous experience in physical and biological inverse optimization of intensity-modulated radiotherapy treatment
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 4 days ago
process models for electrified methanol processes under fluctuating power supply from renewable sources # Simulation and optimization of the operating behavior of flexible systems, including control and
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, troubleshooting, and optimization of building automation and energy management systems. Provide technical guidance and escalation support for complex control issues involving HVAC, electrical, and life safety
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 23 hours ago
Summary of Work for this Position Analyzes building automation and control systems to achieve optimal operation or energy efficiency. Will make recommendations for modifications based on analyzation
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into model-predictive control (MPC) or reinforcement learning (RL) frameworks to compute optimal exoskeleton assistance in real time. Validating the developed methods in human experiments using motion capture