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Field
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specific requirements: a) Experience in the application of data analysis and machine learning methods to scientific data (e.g. multivariate analysis, chemometrics, neural networks, classification
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network discovery and individualized circuit targeting, multimodal concurrent brain stimulation-recording, and computational modeling. We bridge invasive approaches, including intracranial electrical
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activities, including the collection, analysis and documentation of qualitative and quantitative data. The role involves preparing research reports, developing data collection tools, communicating project
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semi-quantitative network methods (socio-technical configuration analysis, STCA), and contribute to the project's methods development compare cases across sectors and across high- and middle-income
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of novel diabetes therapies Precision medicine for Type 1 and Type 2 diabetes Human pancreas imaging and spatial biology Digital pathology and computational tissue analysis Clinical decision support using
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experience in RF, microwave or high-frequency electrical measurement and characterisation. Practical experience in the measurement and analysis of fast transient or pulsed electrical signals. Strong hands
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well in a team Communication skills in an international work environment The following would also be advantageous: Experience with network analysis in microbial ecology Knowledge of the reconstruction
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across Europe and the UK and sent to Newcastle University for analysis using the Newcastle MSI-Plus Assay to screen for urothelial and endometrial cancer (https://pubmed.ncbi.nlm.nih.gov/41138669
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software, analytical platform, chemistry and microbiology laboratories. **Main contacts (CNRS internal and external network):** JH Renault (ICMR), Véronique Eparvier (ICSN), Maria Halabalaki (NPMC, Athens
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, genomics and systems medicine Access to national and international collaborators and research networks Support to publish high-quality research in peer-reviewed international journals and to present your