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: The doctoral candidate will perform computational analysis of a combination of multi-omics data from the gut microbiomes of patients with Alzheimer's disease or Parkinson's disease. The candidate will use state
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study and other ongoing translational initiatives to develop a voice-based digital health solution to alleviate the diabetes burden. Project objective The PhD candidate will work at the interface
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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and epidemiological characterisation of cardiovascular risk among people living with T1D, using multimodal data in the large SFDT1 cohort study. This work will lay the groundwork for developing novel
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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
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number of techniques routinely used in the lab including histology, confocal microscopy and image processing. Prior expertise in cell culture, image analysis and coding would be highly appreciated. Part of