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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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, to characterize immune cell dynamics in murine models of inflammation and cancer. RESPONSIBILITIES: Developing and performing computer simulation of MRI contrast of labelled cells and tissue Labeling and tracking
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Research Project“ Transforming Cardiac Research: Visual Exploration and AI Prediction Modeling of Real-Life, Multi-Modal Data” as a PhD-Position in machine learning. You will work alongside leading experts
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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qualification (usually PhD). Tasks: The aim of the project is to design, model, fabricate and test a wireless micro-sensor which uses magnetic fields for sensing in biological soft tissues. For further
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-assisted simulation framework by providing accurate high-fidelity numerical data for training and validation of surrogate models for multi-disciplinary design and optimization. · Participating in
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below? Are you our future colleague? Apply now! Experience and skills · You have a strong interest in terrestrial ecosystems modelling, vegetation demography, plant physiology, and climate change
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a powerful way for assessing forest stress and disturbances over large areas and to monitor forest vitality over time. This research uses remote sensing technologies together with physical models and
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susceptible to SM, VWC, and atmospheric delay. As a result, the objective of this PhD project is to develop models able to fuse backscattering and phase information to estimate SM and VWC more accurately. The
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mechanisms. The overall goal of the research project is to develop process understanding and parametrizations that lead to improved, energetically consistent, climate models. Close collaboration with the other