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short-term physiological responses of tree species and modified long-term dynamics of the whole ecosystem. On the other hand, vegetation demography models are numerical tools formulating forest processes
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, biochemists and technicians. The multidisciplinary research in our group covers a wide range of topics from radiobiology, radiation physics and space research to radiation therapy. The radiobiological modelling
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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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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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