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research methods applied to urban contexts.• Experience with spatial modelling software (Metashape), geographic information systems (ArcGIS Pro), creative tools(Photoshop), and quantitative (SPSS) and
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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develop open-source, surrogate models of land-atmosphere exchange, at various spatial resolutions and using various methodologies, to contribute to a better understanding of the carbon and climate impacts
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and immune trafficking models. High-Resolution Imaging: Proficiency in spatially-resolved multiplexed imaging and confocal whole-mount tissue analysis. scRNA-seq: Experience designing 10x Genomics
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. Description: The successful post-doc will participate in a program which focuses on understanding the Martian atmosphere, its variability, and its interaction with the surface through observing and/or modeling
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Design, develop, and implement advanced algorithms, models, and software tools for spatial data analysis, machine learning, and AI-driven geospatial applications Lead and collaborate on interdisciplinary
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, as a finite production factor, functions concurrently as an economic resource, environmental capital, and spatial determinant of investment decisions. The primary objective is to evaluate
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, the project will: Develop novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for spatial structures, physical laws, high-dimensional imaging
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background in multivariate statistical analyses (e.g. R or comparable software) • Proven experience in GIS-based spatial analyses • Experience in species distribution modelling • Track record of peer
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an emphasis on ecosystem dynamics, behaviour, spatial modelling and evaluation of ecological aspects of management measures. The candidate may start as soon as possible or after agreement. The position is