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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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: 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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health tools. Basic proficiency in data analysis (Python or R); experience with speech analysis libraries or NLP is an asset. Strong scientific writing skills and a collaborative spirit. High motivation
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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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. We will link molecular programs in specialised myonuclei to sensory-motor coordination sensory-motor coordination through eye-tracking and visual acuity assessments (collaboration with NeuroPSi Paris
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and neural computation. By leveraging the rich data repository on the larva’s neural connectome and muscular structure, the project seeks to create accurate simulations that can inform biological
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Wikibase instance Curate and model historical migration datasets within the dedicated Wikibase instance Contribute to the design of ontologies and metadata schemas for the knowledge graph Develop data-driven
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Description of the offer : This PhD project supports the exploration of Vertical Compute’s vertical magnetic device concept. Thanks to the inherent high speed of magnetics and the vertical data
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be expected to teach advanced courses in Artificial Intelligence—particularly in machine learning, statistical learning, natural language processing (NLP), symbolic AI, computer vision, and related
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Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices