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genetics, genomics, imaging processes, computational biology and biochemistry. Our goal is the deep and detailed understanding of fundamental mechanisms in plant biology that may then also be used to develop
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. Philion and S. Fidler, “Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,” in Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28
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of the domain, while the pre-processing step of geometry manipulation and mesh generation is one of the most important efficiency bottlenecks in such methods. The challenge is more prominent in modern, real-world
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Professor in Medical Imaging. The Faculty of Science, Technology, and Medicine at the University of Luxembourg strives for excellence in the education and research of medicine, biomedical sciences and allied
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. Required Skills and Candidate Profile The project is intended for a candidate with: ➢ Skills in medical image processing and deep learning adapted to clinical applications. ➢ A good knowledge of Python
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Professor in clinical imaging. The Faculty of Science, Technology, and Medicine at the University of Luxembourg strives for excellence in the education and research of medicine, biomedical sciences and allied
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Professor in clinical imaging. The Faculty of Science, Technology, and Medicine at the University of Luxembourg strives for excellence in the education and research of medicine, biomedical sciences and allied
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opportunity for an outstanding scientist to establish an independent research program at the interface of biology and computer sciences, in one of the five major DYNABIO-affiliated institutes (C3M, iBV, IPMC
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micro-environment (dendritic cells and anti-tumoral T lymphocytes) and to decipher how immunotherapies impact on these processes. The main objectives of this project are: – to implement single cell RNAseq
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friction models. Integrating Experimental Data: Collaborate with experimental teams to incorporate data from calcium imaging, confocal microscopy, and high-resolution video recordings. Use experimental data