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Employer
- Autonomous University of Madrid (Universidad Autónoma de Madrid)
- Forest Science and Technology Centre of Catalonia
- ICN2
- ISGLOBAL
- Institut de Recerca Biomèdica de Lleida, Fundació Dr. Pifarré (IRBLleida)
- Institut d’Investigació Biomèdica de Girona Dr. Josep Trueta (IDIBGI-CERCA)
- Institute for bioengineering of Catalonia, IBEC
- Instituto de Neurociencia Avanzada de Barcelona
- UNIOVI
- University of Deusto
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Field
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. Process and analyze neurophysiological, physiological, and behavioral data. Develop and maintain reproducible analysis pipelines. Perform signal processing, artifact removal, feature extraction, statistical
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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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: Design and conduct laboratory experiments. Characterize materials using advanced analytical techniques (XRD, SEM-EDS, ICP-OES/ICP-MS, FTIR, Raman and thermal analysis). Process and statistically analyse
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will begin from June 2026. Education and Background PhD degree in a relevant quantitative discipline such as Bioinformatics, Statistics, Mathematics, Data Engineering, or Biomedical Engineering
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and sample tracking into reproducible end-to-end pipelines. Develop and apply computational pipelines for image processing, cell segmentation, debarcoding and spatial statistics. Close the experimental
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achievement in epidemiology or environmental health; experience with health impact assessment is an asset Experience with statistical analysis and managing complex data in R Excellent quantitative and
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, Conservation Biology, Environmental Sciences, Agronomy, or a related discipline. 4. Advanced written and spoken English. 5. Knowledge of statistical analysis software, particularly R or equivalent tools, and
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temporal resolution. Background in network science, statistical physics and complex systems. (Optional) Familiarity with information-theoretic measures (Transfer Entropy / Symbolic Transfer Entropy) and the
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/Qualifications - Demonstrated expertise in advanced statistical techniques, such as: Multilevel modeling (HLM, mixed-effects models) Longitudinal and panel data analysis Structural equation modeling (SEM) Causal
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computing and reproducible research. (Optional) Experience in time-series analysis, with explicit attention to intraday temporal resolution. Background in network science, statistical physics and complex