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acts as an autonomous agent collaborating to achieve global performance goals such as indoor air quality, thermal comfort, and energy efficiency. This PhD offers a unique opportunity to work at the
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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure
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. This is achieved by working closely together with the different wind farm operators within the Belgian offshore zone, e.g., Parkwind, Norther, Otary. The main focus of the department is on performance
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the performance and explainability of Artificial Neural Networks (ANNs). In collaboration with our medical project partners, we hope to leverage the results of this ANN-based study to better understand social
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performance. Experimental Validation: Conduct laboratory testing of fabricated PICs connected with off-the-shelf components to validate the proposed concepts. Team-based Collaboration: Work closely with experts
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perform research on the neuronal correlates of the adaptation to accented speech. Research methods include electroencephalography and/or magnetoencephalography to assess neural response to continuous speech
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using in-house cells at the Swiss Light Source (SLS) and at the European Synchrotron (ESRF) and analyse the results. They will perform Nano Raman/SERS experiments and investigate the photochemical
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measurements from optical techniques such as white light interferometry. The selected candidate will contribute to the group’s R&D output and carry out the following tasks over the 4-year PhD: Perform 3D
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distribution of active sites and guide future catalyst design. Structural insights will be correlated with catalytic performance metrics, provided by project partners, to identify the role of material structure
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or pharmaceutical sciences, or will have obtained it by the time you start to work. Outstanding academic study performances according to ECST grading scale. FELASA C degree (or EU equivalent) for possible handling