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degree in Economics (Master of Science degree of advantage) ; Demonstrated experience in programming languages such as Stata, R or Python. Previous knowledge of Dynare, GIS and/or Matlab applications and
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comparable field Very good knowledge of quantitative research methods in medicine or health sciences Demonstrable subject-specific programming skills (e.g., R, Python, etc.) Experience with database usage (e.g
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Health, Data Science, Remote Sensing, Geomatics or a closely related discipline•Strong analytical and programming skills (e.g. Python or similar)•Experience in at least two of the following areas
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of tools such as R, Python, GIS, Git or similar data-science software. Solid experience with community data and biodiversity monitoring. A broad ecological background, ideally including plants and
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, Environmental Science, Agronomy, Plant Science, Soil Science, Agricultural Engineering, or related quantitative field. • Demonstrated experience in GIS-based spatial analysis. • Experience with quantitative
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and AI algorithms Solid programming skills in Python and familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) Experience working with geospatial data (e.g., geopandas
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, project and program evaluation, and report writing. Data science and Geospatial Analysis skills, including coding (e.g., Python, R), inferential statistics (e.g., MATLAB, STATA), predictive modeling, GIS
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Required Qualifications PhD in Animal Science, Environmental Science, Agronomy, Plant Science, Soil Science, Agricultural Engineering, or related quantitative field. Demonstrated experience in GIS-based
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designers, GIS specialists, and stakeholders to ensure tools meet user needs. Documentation & Support: Produce technical documentation and provide support for internal and external users. Minimum Requirements
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
or territorial studies. Preference will be given to candidates with aptitude for working in disaster risk management environments supported with GIS and Machine Learning, basic programming skills (e.g., Python, R