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the field of the airway. Management, analysis and interpretation of clinical and research data, including the application of bioinformatics and statistical analysis techniques. Coordination and monitoring
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(PIT-tags, hydrophones, geophones, etc.). 2) Modeling and data analysis: - Proficiency in GIS tools (QGIS, ArcGIS) and hydraulic modeling software (HEC-RAS, TELEMAC, Mike). - Advanced programming (Python
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advanced data analysis. Most of the research will be carried out in the battery research laboratories, which are equipped with state-of-the-art facilities for materials synthesis, characterization (XPS
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transformation, machine learning, and data analysis applied in logistics and supply chain management; support graduate-level teaching activities for both the Supply Chain Management residential (SCMr) and Supply
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computational methods for single-cell and genomic data analysis, in collaboration with the lab’s methods-development efforts. • Develop and apply flow cytometry, molecular biology, and cell biology assays
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., video, audio, artifacts). Experience in using qualitative data analysis software. Experience in creating interactive design prototypes and data visualizations. Experience in machine learning or generative
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, on the muon spectrometer Level 1 MDT trigger. The applicants will be expected to engage in a physics measurement through data analysis as well. Applicants should send a curriculum vitae, a list of publications
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23 Sep 2026 Job Information Organisation/Company Gustave Roussy Department INSERM U1279 Research Field Biological sciences » Biological engineering Physics » Biophysics Engineering » Biomedical
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knowledge of data analysis and processing, programming, and development of analytical models. Experience with databases and quantitative analysis tools. Ability to work with large datasets and computational
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multidisciplinary investigators, and establish an independent research direction. As a successful candidate you will: Lead computational analysis of single-cell/single-nucleus RNA-seq, ATAC-seq, and multiome datasets