19 parallel-processing-bioinformatics positions at CNRS in computer-science in France
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scientists: Charlene Lasgi and Leanne De Koning). The bioinformatics part will be done at the IBPS with the PhD student in collaboration with M Doulazmi, IR CNRS (0000-0002-0313-1490) an expert in
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mixtures, including information retrieval, random access, approximate search, querying and filtering, encryption, compression, and many other information-processing tasks. Our team is looking for a talented
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Sciences of the University of Strasbourg. Close collaborations with the various project partners are also planned throughout the PhD. A dedicated computer equipped with high-performance GPU cards will be
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organismal levels • Gene expression analysis (histology, scRNAseq data minining) • Phenotyping using behavioural setups • Acquisition and segmentation of image datasets • Bioinformatic data analysis (genome
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biology, genetics, single-cell and spatial transcriptomics, advanced imaging, and bioinformatics. The main objective will be to identify the gene networks involved in muscle morphogenesis, reconstruct
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macrophages recognize, deform and internalize microplastics and other microparticles. In parallel, the project will incorporate a design-driven research perspective exploring how forms, objects, images and
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CNRS 6144), a leading laboratory in process engineering, particularly in electrochemical engineering for environmental applications such as water treatment and reuse, as well as the valorization
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catalytic processes in homogeneous solution and on surfaces. EMPRe team students are trained in the synthesis of ligands and transition metal complexes. They then apply methods of molecular electrochemistry
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bachelor's students and ensuring the proper maintenance and operation of the synthesis lab in accordance with the recommendations provided by funding agencies and the laboratory administration. • Develop
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the growth of carbon chains. • Collaborate with astrochemists and observers to validate theoretical predictions. This position will focus on modeling dust production in supernova explosions, a key process for