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Connectomic analysis of multiscale biological cellular networks

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The analysis of complex networks is a fascinating field with incredibly varied applications: social networks interactions, logistics, transport, telecom and computing infrastructures etc. It is also a cornerstone of neuroscience, where biologists seek to understand the relations between measured functions and the brain organization. At the most fundamental level, this implies understanding how the topology/connectivity of the neuron network determines higher scale functions and vice versa. Interestingly, few people know that there are as many cells in the human skeleton as there are in the brain and in both cases, cells are highly interconnected. The precise biological role of this network and its topology is still very poorly understood and it is therefore tempting to apply similar ideas developed in the general framework of complex networks analysis to bones. Such approaches are expected to have a strong impact in the biomedical community.

We are currently seeking a talented MSc or final year Engineering student in one of the following topics : physics of complex systems, bio/medical imaging and signaling or applied mathematics with a solid training in Python programming and image processing. Your main tasks will be to optimize the current image processing pipelines using morphological models and machine learning tools and to implement graph analysis including geometry and symmetry network characteristics.

This Master internship is expected to lay the ground for a PhD funded by a HFSP grant recently obtained with colleagues from McMaster University (Canada) and the City College of New-York (USA). Within the framework of this international collaboration, you will also strongly be encouraged to spend time at the different partner’s labs in Canada and the US to benefit from our mutual expertise and broaden the scope of your research. The major biomedical application of this project is the analysis of the cellular porosity network evolution as a function of mineral depletion in bone in a lactating mouse model.

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