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decade, providing opportunities to mine big data to learn more about the drivers of AMR in humans. Our work includes computational analysis of antibiotic resistance and microbiomes, statistical analysis
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candidates can start as soon as possible and ideally by early 2026. The overreaching aim of REC is to generate a coordinated analysis of long-term ecological data to understand the drivers and consequences
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data has increased massively in the last decade, providing opportunities to mine big data to learn more about the drivers of AMR in humans. Our work includes computational analysis of antibiotic
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the entire population. The project utilises advanced statistical methods such as multilevel models (mixed models), fixed-effects models, cluster analysis, and sequence analysis. The selected researcher is
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, developmental biology, genetics, biomedicine, or another appropriate field. Previous experience in confocal imaging and image analysis, scRNA-seq data analysis, or genetically engineered mouse models is
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2025, or as agreed, in a fixed-term contract until 31.8.2029. Background The positions are opened in the HIP CMS experiment group, which contributes to the analysis of data from the CERN CMS experiment
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approach that includes advanced bioimaging and image analysis, cell biology and genetics, and omics technologies. Qualifications We invite applications from candidates with a background in cell and
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: Has a doctoral degree - the degree requirement must be met by the beginning of the employment Has a strong methodological background in agent-based modelling, systems dynamics, network analysis
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, to uncover convergent gene regulatory mechanisms, with the goal of informing therapeutic strategies. Tasks The tasks will include one or more of the following: Analysis of data collected from developing
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microbiome from clinical patient samples Computational analysis and integration of functional microbial genomics datasets from next-generation sequencing methods. Supervision and teaching of students and