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LiDAR-based ecology. We're looking for candidates with strong technical skills and ecological interest—people who want to use LiDAR, AI, and spatial modeling to advance our understanding of vegetation
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modelling is not required. However, a strong ability to perform 3D spatial visualization, particularly when working with fragmentary or incomplete fossil data, is essential. Languages: French and English
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électriques ou électromagnétiques (Arnason et al., 2025, e.g. Vilhjalmson et Flovenz, 2017, Lévy et al., 2019). L'objet d'étude concernera la caractérisation à haute résolution spatiale des systèmes volcaniques
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models, statistical signal processing, statistical theory and computational statistics, and probability theory, with applications in areas such as medicine, environmental research, and financial
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approaches. The PhD will develop and apply optimization-based energy system models to analyse whether spatially coherent urban and energy configurations can be operated efficiently under realistic physical
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applications, agricultural monitoring and modeling, Agro-AI/ML, or digital twin. Instructions to Applicants: For full consideration, applicants must apply for the Research Assistant Professor at https
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community; support multi‑omics data integration and analysis across multiple research groups; and collaborate on the development and maintenance of computational pipelines for spatially resolved
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. These data will be integrated into TemisFlow (Themis) thermal models to reconstruct the thermal and subsidence history of the basins. The modeling will quantify the distribution of heat flow during
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, Digital Soil Mapping, Remote sensing (COPERNICUS data ecosystem), spatial data modelling, spatial analysis, neural networks, large scale datasets management with GIS, cloud computing, Big Data tools. You
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, or probabilistic modeling, and be proficient in Python and modern machine-learning frameworks (ideally PyTorch). Experience with single-cell transcriptomics, epigenomics, proteomics, spatial omics, or multimodal