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candidate, with a strong background in the development of machine learning methods for bioinformatics. The project focuses on the development of new neural network architectures to perform inference
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department and the Plant Reproductive Strategies (SRP) team. Our team focuses on the evolution of plant reproductive systems, using diverse approaches including theory, experimentation, bioinformatics, and
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the southern area of Grand Paris. We offer an international, highly collaborative research environment with access to state-of-the-art core facilities, including advanced imaging, genomics, and bioinformatics
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, clinical and histological data in a translational framework. Main activities: - Bioinformatic analysis of WES and RNA-seq data. - Somatic variant detection and annotation. - Statistical and clinical
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targets. Main activities: - Bioinformatic analysis of WES and RNA-seq data. - Variant calling, annotation, and mutational signature analysis. - Differential gene expression and pathway analyses
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biology, bioinformatics, computer science, biology, or a related discipline, Strong interest in applying quantitative approaches to complex biological and biomedical questions Solid computational skills
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resonance imaging (MRI) or focalized X-ray irradiator devices will be a plus. Experience on bioinformatic analyses (WES/WGS, (sc)RNA-Seq, ChIP-Seq, ATAC-Seq, Proteomics, Spatial Transcriptomics) and/or R
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immunology and bioinformatic analysis (e.g., scRNA-seq) (highly desirable). Skills in in vivo models are an advantage. Ability to work independently and collaboratively within a diverse, international team
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, and figures in English. Fluency in written and spoken scientific English. Specific Requirements Strong interdisciplinary interactions with both the biology research team and the CIML bioinformatics