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with ecosystem service models and spatial datasets. Key Competencies Strong programming skills (Python/R/JavaScript) for tool and interface development. Ability to implement or learn GeoTOPSIS/VectorMCDA
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combining multi-source, remotely-sensed data streams towards improved biomass, carbon-pool sequestration, multilayer fuel load, mapping key fuel variables and fuel models through data fusion that can be
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 9 days ago
of Computational Biology (ICB) , as part of the Computational Health Center at Helmholtz Munich, is globally recognised for innovations in data analysis and modelling of biological systems and diseases, anchored
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) government, industry, and local NGO’s. Your main contribution will be the development of a spatially explicit agent-based model of the society of the Metropolitan Region of Amsterdam, simulating circular
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to cutting-edge research on spatial reasoning, semantic technologies, and interdisciplinary AI for geosciences and geography. Where to apply Website https://www.academictransfer.com/en/jobs/356998/phd-position
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to identify the historical, structural, and contextual drivers of disease risk and inequity, and map pathways and interactions among determinants to inform disease mapping and modelling. The RA will lead the
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. The candidate will have access to advanced platforms for single-cell and spatial omics, 3D tissue modeling, bioreactors, and in vivo models. The successful fellow will also contribute to collaborative efforts
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-Zero X (NZx) initiative, which is building on the impactful Net-Zero America (NZA) study (https://netzeroamerica.princeton.edu/the-report) that developed uniquely-granular spatial, temporal, sectoral
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-cell sequencing and spatial transcriptomics is preferred. This position will be an excellent opportunity to gain experience performing basic and translational research using patient-derived specimens and
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fish larvae. Although the importance of drift is well established, many of its underlying dynamics—particularly its spatial and temporal variability—remain poorly quantified. This knowledge gap largely