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Chemical Engineering in the Faculty of Applied Engineering is looking for a full-time (100%) doctoral scholarship holder in the field of machine learning for circular polyurethane design. Position You
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. Potential application domains include autonomous systems, robotics, flexible asset (e.g., storage, electric vehicles) management in smart grids, etc. You will publish scientific articles related to
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transfer, and adaptation under non-stationarity. Potential application domains include autonomous systems, robotics, flexible asset (e.g., storage, electric vehicles) management in smart grids, etc. You
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, networking, and signal processing. You have at least intermediate knowledge of machine learning algorithms. Knowledge of satellite communications, wireless sensing, radio propagation, optimization, or
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analysis, optimization, and machine learning techniques is a plus. Knowledge of machine learning libraries (e.g., PyTorch or TensorFlow), SDR hardware (e.g., USRP) and software (e.g., GNURadio
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of intelligent control algorithms for inland waterway vessels, using machine learning, with the aim of controlling the vessel in an optimal and efficient manner. In this context, control is formulated
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qualities are in line with the faculty and university research policies . You act with attention to quality, integrity, creativity and cooperation. You have a strong interest in machine learning
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research the next generation of automatic generation of mechanisms and the optimization of their performance. This movie provides a general introduction to the machine design research within Cosys-Lab
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one of the 15 Doctoral Candidates in the NeXED Marie Skłodowska-Curie Actions (MSCA) Doctoral Network. For more information about NeXED, see https://www.nexed.eu . Your research will focus on the