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methods to biological and clinical research datasets. Primary responsibilities include analyzing bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics data; developing and maintaining reproducible
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | 14 days ago
, generating and analyzing high-dimensional data, and integrating single-cell insights with complementary datasets produced within the project. You will: Design and execute single-cell and/or spatial
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Foundation (FAPESP), and combines statistical analysis, spatial methods, and qualitative research. Georeferenced data from the Military Police and the Municipal Secretariat of Urban Security will be used
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addition to holding a PhD, you must have a strong analytical background and experience in quantitative ecology, spatial analysis, handling large and complex datasets, and proficiency in programming (e.g., R or Python
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to high-dimensional omics datasets. Familiarity with transcriptomic analysis tools (e.g., Seurat, Scanpy, DESeq2). Experience with spatial transcriptomics and multi-modal data integration is highly
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to establish mechanistic insight and therapeutic direction. The Research Associate will contribute to project leadership through experimental design, data analysis, and dissemination of findings through high
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collaborative research environment to analyze unique spatial data in an innovative manner. You will develop and perform cutting-edge bioinformatic analysis integrating different multiplexed spatial data, and gain
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the fundamental factors governing cation mobility in aluminosilicate materials through an integrated experimental-theoretical-computational approach. The research will probe the spatial extent and timescales of ion
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leading role at the international level, for example in the field of plant and microbial data management, in the evaluation of new methods of genome analysis, in the integration, interpretation, and
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through multi-modal sensing, autonomous UAV platforms, and advanced AI-based analysis. A central focus is the detection of defects in bridges and viaducts using X-ray, LiDAR, visual and acoustic data