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Field
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for predictive and prescriptive urban data analysis. Experience in visualizing and analyzing spatial and functional interactions within urban infrastructure. Personal and Organizational Skills Ability to model
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for collecting data on environmental and health parameters (air quality, noise, mobility). GIS Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial determinants of urban
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main tasks will consist of: Independent research of high international quality, including publication. Analyzing sequencing data (e.g., scRNA-seq, snRNA-seq and spatial transcriptomics) from various
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tools, data science techniques, and spatial analysis to leverage big data from cities and model their evolution. Main Tasks and Responsibilities: Collect, clean, and structure large volumes of urban
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and strengthen societal capacity to address the climate and biodiversity emergencies. The project will generate spatial-temporal datasets from various sources including Spaceborne Satellites, Drones, In
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candidate will contribute to projects involving participants with implanted intracranial electrodes and wearable non-invasive sensors, with a focus on memory consolidation, spatial navigation, and neural
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The successful candidate will be responsible for developing computational and systems biology approaches to analyze spatial omics data and single-cell omics data (e.g., scRNA-seq, scATAC-seq, single
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emergencies. The project will generate spatial-temporal datasets from various sources including Spaceborne Satellites, Drones, In-situ instruments, Land-Management, Soil & GIS databases that can be processed
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the research group of Professor Klaus Nordhausen in the project “Signal recovery in noisy spatial data”. The research group develops modern and efficient multivariate statistical methods tailored
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, RNA seq, single cell sequencing, spatial transcriptomics), bioinformatics tools and human studies. Your profile: PhD in bioinformatics, oncology or computational biology profound experience in system