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an interdisciplinary environment as well as excellent facilities for remote sensing research and numerical simulation and inversion Opportunities to being part of the national and international scientific community PhD
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 22 hours ago
or Geoinformatics, or related areas and to be enrolled PhD. Candidates will be assessed according to the project team’s needs regarding geospatial data and remote sensing for analysis, interpretation, and application
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responds to climate change in the past and present to improve future predictions of sea-level rise and Earth system feedbacks. The work combines collection of field data, remote sensing, and modelling in
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Specific Requirements As a PhD researcher, you must have: A completed (or about to be completed) MSc degree in geo-information science, remote sensing, spatial statistics, or a similar relevant field. A
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(e.g. computer vision, deep learning, AI) and green life sciences (e.g., remote sensing, crop modelling, and food security), within the European funded project AgriscienceFM (Horizon programme), which
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analytics, geographical information science, satellite positioning, ubiquitous positioning, photogrammetry and remote sensing, geodesy and geodynamics, environmental monitoring, geo-hazards studies
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international expert groups. Contribute to scientific writing, grant applications, and doctoral research activities. Where to apply Website https://jobs.vhir.org/jobs/7564587-clinical-researcher-in-paediatric
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Institut de Recherche pour le Développement (IRD) | Sete, Languedoc Roussillon | France | 4 days ago
associations in Oceania, Africa, Latin America, Southeast Asia, the Pacific Ocean, and the Mediterranean basin. An appealing opportunity The PhD candidate in Economics will conduct an in-depth study of
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that does not reflect local reality and thereby create unfair comparisons. Your work will include measurements of greenhouse gases (CO2, CH4, N2O) using drones and various sensors, as well as remote sensing
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into answering counterfactual questions. Using remote sensing multimodal time-series data and Earth foundation model embeddings, you will design and develop causal machine learning models tailored for dynamic