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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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applications which is hindered by the lack of a molecular understanding of their formation process. This is particularly true for zeolite synthesis which is characterized by a very complex reaction network in
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(Artificial Intelligence and Epidemic Modeling to Prepare Hospitals for the Next Respiratory Pathogen with Pandemic Potential). Project Overview The COVID-19 pandemic exposed critical gaps in our ability
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model-based control tailored to systems like NudgeFlow. The framework decomposes the global control problem into smaller local problems for each zone or room, enabling independent optimization with local
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trained in the theoretical modelling of the chiral surfaces. You are a motivated researcher with a Master in physics, chemistry, nanotechnology, or related fields. You have knowledge of scanning tunneling
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methods to study dynamic cellular processes (live calcium imaging, pathological protein assembly, imaging of signal cascades) at spatial levels ranging from a single molecule to (entire organs of) model
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. System Modeling: Develop and refine photonic system models incorporating key quantum mechanisms. Use simulation tools (Lumerical, Synopsys, Matlab, Python, …) to validate architectural feasibility and
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-motivation, flexibility and team spirit. Experience with techniques such as cell culture, CAM model, qRT-PCR, fluorescence microscopy and/or bioinformatics would be a plus. Your teaching competences are in
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data collected from a geothermal borefield in Brussels, modelling activities of subsurface heat transfers between borehole heat exchangers, and the development of strategies for the optimal integration
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-making (e.g. during operation, but also during design) to prevent over-consumption of fatigue life while balancing optimal production. The monitoring of fatigue loads along the entire substructure is a