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- Autonomous University of Madrid (Universidad Autónoma de Madrid)
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- Institut d’Investigació Biomèdica de Girona Dr. Josep Trueta (IDIBGI-CERCA)
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Field
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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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Description The post-doctoral fellow will work on research projects related to the network applying a data management plan and statistical analysis plan design, epidemiology, causal inference, semi-parametric
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Institut d’Investigació Biomèdica de Girona Dr. Josep Trueta (IDIBGI-CERCA) | Spain | about 2 months ago
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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in the academic domain. Fluent use of Statistical Software like SPSS.) Specific Requirements Publications in journals of the field with high impact factor, preferably related to the Self-Validation
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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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. The candidate is expected to plan, gather, analyse, and publish data based on such analyses in an independent and original manner. Experience with appropriate statistical tools (Python, Matlab, R etc) and methods
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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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. Knowledge of chemical labeling techniques. Proficiency in office software, with a solid command of Microsoft Office applications (especially Word, PowerPoint, and Excel). Knowledge of statistical software