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of more efficient cancer detection methods and revolutionary therapies. The center is looking for A PhD for the project “Intraoperative assessment of resection margins in breast cancer surgery by Raman
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block within this process. You will be embedded both within an experimental and computational team, providing a unique atmosphere where there is expertise to develop the deep-learning models while having
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1-D and 2-D modelling approaches fail to capture the complex three-dimensional effects critical to high-frequency, high-efficiency operation in modern converters. The PhD candidate will: 1
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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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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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. 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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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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ventricle. The Fontan circulation is created by a two-stage surgery where the venous return is connected directly to the pulmonary circulation. The heart acts as a single chambered heart to produce
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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
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-pathogen interactions using in vitro model systems mimicking chronic diseases. The project foresees ample collaborative opportunities with research groups in the MICRO-PATH consortium, spanning