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with R, statistical and spatial analysis Excellent communication and teamwork skills Excellent organizational skills Experience with field work in post-disturbance forest conditions (desired) Experience
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3D cell cultures under several perturbations Develop and apply methods for the analysis of the cellular proteome both at cell type, and single-cell level, based on imaging results and recent spatial
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://pritykinlab.princeton.edu) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi-modal single-cell, spatial and genome editing
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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managing human subjects research and handling sensitive data is preferred. • Strong quantitative skills, including proficiency in regression modeling, environmental mixtures analysis, and spatial methods
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://pritykinlab.princeton.edu ) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi-modal single-cell, spatial and genome editing
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3D cell cultures under several perturbations Develop and apply methods for the analysis of the cellular proteome both at cell type, and single-cell level, based on imaging results and recent spatial
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with partners across Europe: data sharing, code exchange, joint publications and reporting. Your qualities You hold a PhD (or near completion) in Soil Science, Environmental Modelling, Biogeochemistry
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or spatial profiling; Mouse genetics and in vivo experimentation; Lineage tracing, clonal dynamics, or immune repertoire studies Candidates should hold (or be close to completing) a PhD in a relevant field
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: Geographic Information Systems (GIS): Knowledge of GIS for spatial analysis, including tools such as ArcGIS or QGIS. Publication & Presentation Experience: Experience in publishing research in peer-reviewed