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6 Jan 2026 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique de Grenoble Research Field Biological sciences Computer science Mathematics Researcher Profile First Stage Researcher (R1) Country France Application Deadline 26 Jan 2026 - 23:59 (UTC) Type of...
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analytical and bioinformatics tools to analyse and interpret data To establish workflows for the collection and analysis of samples, human stem-cell-derived brain organoids, and to develop experimental
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, Interactive and Cognitive Systems, Distributed Systems, Parallel Computing, and Networks. The host team, DAISY, is a joint CNRS, Grenoble INP, and UGA research team handling research challenges
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bioinformatics. The main responsibilities include: High-throughput sequencing: Applying long-read sequencing technologies (Oxford Nanopore) to quantify DVG populations in cells and virions without PCR bias (Direct
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the genetic material of incipient species can dissolve species boundaries, a thorough comprehension of the evolution and regulation of meiotic recombination during the speciation process is central to our
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analytical and bioinformatics tools to analyse and interpret data - To establish workflows for the collection and analysis of samples, human stem-cell-derived brain organoids, and to develop experimental
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research unit of CNRS, Grenoble INP, and Université Grenoble Alpes, is a center of excellence in materials science and innovative processes. It spans diverse fields—from metallurgy to nanomaterials and
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available for experiments. Tracking radical species in oxidative water treatment processes Oxidative treatments are commonly used in water treatment, either for disinfection or micropollutant degradation
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strong potential as well for enhancing the quality of produce and positively influencing the sustainability of agricultural processes. The market of agricultural robots grew at a rate of 19.3% from 2021
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on electrophysiological approaches (MEEG, iEEG) and signal processing, while in Maastricht, the partner team provides ultra-high-field imaging (7T and 9.4T fMRI) and AI-based modeling. The PhD student will be enrolled