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group: MARIANNE (https://team.inria.fr/marianne/). The MARIANNE project-team pursues high-impact research in Artificial Intelligence with a focus on data and models for computational argumentation in
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(large scale heterogenous data synthesis, meta-analytic studies, conceptual synthesis) Experiences and interests in shaping modern team science research and interest in super-visioning & coordinating
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the Research Facilitator team and the FSTM's financial controllers to provide consistent, strategic project support Further information: Please contact the team leader of the Research Facilitators team, Your
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analysis of biomedical data and bioscientific programming for a project on the study of neurological disorders. The candidate should have experience in the analysis of large-scale biomedical data (e.g
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, Experience and Qualifications PhD in biochemistry, Biomedical Sciences or Chemistry. Mass spectrometry-based proteomics. Data analysis of large proteomics datasets. Experience in cell culture and molecular
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the analysis of large-scale health data, to systematically integrate evidence and identify patterns across diverse health outcomes. The ideal candidate will bring a proven interdisciplinary background
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, IRCAN, ISA). His/her group will leverage large-scale, high-dimensional datasets—such as genomics, transcriptomics, proteomics, imaging, or single-cell data—to uncover fundamental biological mechanisms. We
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within a coherent computational model is currently challenging, due to the typical large dimension and complexity of biomedical data, and the relative low sample size available in typical clinical studies
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, ranging from biological to clinical features. The integration of such heterogeneous information within a coherent computational model is currently challenging, due to the typical large dimension and
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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