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-quantitative histomorphometry and image analysis In vitro endothelial and co-cultur models High content imaging and spatial biology (cooperation AG Schapiro, Heidelberg) Single molecule localisation microcopy
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Student or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d)
at different spatial scales (from plot level to regional level). These indicators are derived using different sensors (field spectrometer, drone with hyperspectral sensor, and satellite imagery) that can be a
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, economic growth, spatial economics. The appointment is for 3 years and will begin September 1, 2026, subject to final budget approval and UAE visa acquisition by the prospective post-doctoral candidate
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geospatial information (land use and cover, biophysical, climate, management practices, etc). • Contribute to the development of spatial and statistical models that describe the interactions between soil and
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Engineering and Geomatics in the field of “Land Use Modelling for Sustainable Urban Planning”. ** According to the European Framework for Research Careers Applicants should have: For the position of Post
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new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks
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networks driving aging and inflammation using cutting-edge molecular and genomic technologies. The project integrates single-cell and spatial transcriptomics, epigenome and whole-genome sequencing, and
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biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms
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on expectations elicited via tailored household and firm surveys (carried out by another team member) and other spatial and physical climate risk data. The goal of this agent-based modeling is to identify
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a