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(R2) Positions PhD Positions Country Poland Application Deadline 1 Oct 2025 - 15:00 (Europe/Warsaw) Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 15 Oct 2025 Is
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We are seeking a Postdoctoral Researcher in Geospatial Urban Big Data to support the analysis of urban dynamics and decision-making in territorial planning. The candidate must be proficient in GIS
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achievement of these objectives. Where to apply E-mail catherine.marchand@umontpellier.fr Requirements Research FieldGeosciences » HydrologyEducation LevelPhD or equivalent Skills/Qualifications PhD in
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sensing, and geodesy approaches Your qualifications: A PhD degree (or equivalent) in Geosciences, Earth Sciences, Geophysics, Remote Sensing, or a related field Background in active tectonics, structural
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the human GI tract. Experimental work may include the cultivation and phenotypic characterization of bacterial strains, or molecular studies involving expression, purification, and characterization
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | about 2 months ago
of Oldenburg Your Profile PhD in marine ecology, finalized by the start of the project Advanced statistical modeling skills including analysis of biodiversity time series and functional traits, evidenced by
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develop innovative solutions based on the analysis of urban data (big data, IoT, GIS) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing
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: • PhD in Geography (Remote Sensing, Geomatics), Computer Science, Agricultural Sciences • Skills and/or knowledge in artificial intelligence (Machine Learning) and programming: proficiency in Python
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using advanced geological modeling tools such as Datamine software, Leapfrog Geo and Surfer. Supervise MSc/PhD students working on related tasks. Publish high-impact papers and contribute to funding
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data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity