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experience in academic writing for publication (e.g. first or co-authored peer reviewed papers) Well-developed statistical software skills (preferably in R, Python, GIS) Competences in quantitative research
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-authored peer reviewed papers) • Well-developed statistical software skills (preferably in R, Python, GIS) • Competences in quantitative research methods – ideally knowledge of several of the following
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, scripts, or lightweight applications using Python, R, or JavaScript Manage research code, data pipelines, and documentation Support the preparation of academic manuscripts, technical reports, and policy
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) • Preferably demonstrable experience in academic writing for publication (e.g. first or co-authored peer reviewed papers) • Well-developed statistical software skills (preferably in R, Python, GIS
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well as European coastal and marine policies (especially EU-MSFD, EU-WFD and EU Nature Restoration Law) Experience in numerical model data extraction with Python and data analysis in R as well as experience in
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related field Demonstrated experience in geospatial analysis (GIS) and proven skills in hydrogeological or hydrological modeling Proficiency in programming (e.g., Python) Ability to handle large datasets
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(past experience with interdisciplinary research is a plus), in particular focusing on hazard, risk and disaster risk reduction GIS qualifications are of major advances Excellent command of English, both
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troubleshooting. Ability to manage, organize, and analyze large genomic datasets using common programming language (e.g., R, Python) and command-line tools. Ability to communicate scientific information clearly
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familiar with spatial analyses, species distribution modelling (SDM), and programming in the R or Python languages to apply these to: Collate and analyse spatial data on MPA boundaries, their protection
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., examples of program codes (Python, R, SQL, GIS scripts, etc.), description or documentation of technical solutions to research problems in which the applicant participated (spatial data processing