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organization. We invite applications from motivated candidates with passion and a strong interest in conducting research and innovation activities on crop modeling, remote sensing, and computer vision to predict
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Archaeology with training in GIS, geophysical surveys, and non-invasive and remote sensing methods, as well as proven experience in archaeological interventions and material analysis. LanguagesENGLISHLevelGood
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of Earth Observation data, with a special focus on GNSS-R data from space. Provide technical support to remote sensing applications related to flood and disaster analysis using satellite observation data
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simulations, remote sensing data processing, and other data-intensive marine applications. Key tasks of the role may include: Maintain and support HPC clusters, storage systems, and data pipelines used in
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, MODFLOW, SWAT, PHREEQC), geographic information systems (ArcGIS, QGIS), remote sensing, and scientific writing. Excellent communication skills in English (spoken and written). Ability to work independently
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planetary science, remote sensing, or lunar/space data analysis. Proficiency in machine learning (supervised/unsupervised learning, neural networks, etc.). Strong skills in data processing (Python, R
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computational innovation to advance archaeological research through AI, HPC, remote sensing, and geospatial analysis. Its mission is to uncover insights into past societies and environments, focusing on urban
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The UCAM-SENS unit is seeking a PhD student to join the European Project IRHIS (Interoperable Remote Health Innovation brought to Scale). About UCAM-SENS UCAM-SENS is a leading research unit
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» Biotechnology Technology » Chemical technology Technology » Production technology Technology » Remote sensing Technology » Pharmaceutical technology Technology » Nanotechnology Technology » Medical technology
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. Other Merits Experience in coastal engineering related projects and/or remote sensing techniques. To 15 points. Personal Interview They will be awarded to the candidates who have obtained the 3 highest