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assessment and evaluation of natural resource planning and management processes. Ability to select and conduct statistical analysis to describe spatial and temporal trends in water quality as a result of
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manipulation studies in collaboration with an interdisciplinary science team. Develop automated data acquisition, calibration, and quality assurance workflows. Develop inversion methods for estimating spatial
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Directions Biological Big Data: data governance, knowledge mining, multi-omics data integration, etc. Tools and Algorithms: sequence analysis, structure prediction, single-cell and spatial omics algorithms
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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | 3 months ago
). Project Description The successful candidate will work on the reconstruction and cartography of the gamma-ray sky using advanced computational and statistical methods. The project involves: Analysis
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Group focuses on biodiversity research, population ecology, and spatial ecology, with the aim of generating scientific knowledge useful for conservation and the sustainable management of agricultural
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spatial analysis. You will design and implement large-scale surveys, manage data collection and cleaning, and carry out rigorous statistical analysis of survey data. You will apply and further develop
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monitoring, telemetry, and community-collected biodiversity datasets, applying rigorous quality assurance and quality control throughout. Conducts statistical analyses using R and/or Python; develops and
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, the ideal candidate will have a background in advanced, 3D cell culture techniques and various canine-focused outcome analyses, including ELISA, RNAseq, spatial transcriptomics, Immunohistochemistry, and
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study how tumor-intrinsic genetic alterations and spatially organized microenvironmental niches jointly shape metastatic progression and therapy response in colorectal cancer. The project is strongly
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team. Perform spatial integration (alignment, upscaling/downscaling) for comparative analyses. Assess the distribution of modeled exposures and health impacts across population subgroups. Contribute