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Field
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in the curriculum with a clear indication of the statistical analyses used, along with the candidate’s role in implementing them. A1.2.) Development of collaborations with international researchers. A2
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obtained will be organized in a structured format and subjected to various statistical analyses. Comparative analysis of the performance of bio-based processes for the recovery of critical metals with
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algorithms; experience in statistical analysis and machine learning tools; experience in executing experimental protocols. Applicants eligibility: Applicants must comply with the eligibility conditions laid
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of natural compounds in the zebrafish embryo/larva model, determination of biochemical parameters (apoptosis, inflammation and oxidative stress responses) in animal samples*; Experience in statistical analysis
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image analysis and the use of geographic information systems in studies to monitor the abundance of stalked barnacles; - experience in univariate and multivariate statistical analysis of ecological data
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areas: Forestry and Agriculture/Earth and Environmental Sciences Skills: - Training and knowledge in Remote Sensing, Spatial Analysis, and Statistical Analysis; - Programming in Python, R, Google Earth
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during fieldwork - Entering field records into databases - Participating in the review, processing and analysis of statistical and/or geographical data (biodiversity, ecosystem services) - Draw up reports
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the demonstration unit • Physicochemical and microbiological characterization of samples collected throughout the tests • Statistical data processing and comparative data analysis • Preparation of reports and
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information can be found at: https://www.dges.gov.pt/pt/pagina/reconhecimento?plid=374 Preferential factors: a) Experience in collecting and analysing documentation and statistical information in the media and
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extraction and subsequent conservation; Support in the forest nursery for seed germination, plant production, acclimatization of micropropagated plants and cultural treatments; Data collection, statistical