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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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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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, 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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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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competitive selection (SELEX), starting from artificial libraries of large numbers (~10^15) of distinct sequences. When the experiment succeeds, variants that perform the selected function well are enriched
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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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will benefit from a first-class environment at CEA LIST with access to a large number of reference tools and a strong experience in design and analysis of secure systems, in particular against fault
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transcriptomics) opens new research horizons on cancer pathologies. These data, of very large dimensions and volume, bring new methodological challenges in terms of statistical and mathematical analysis, as
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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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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems