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Field
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for: Analysis of bulk and single cell RNA-sequencing, spatial transcriptomics, and proteomics datasets Integration of experimental model data with public and clinical datasets Statistical modeling and survival
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, or reproducible research workflows. Knowledge of one or more of the following: GIS, remote sensing, computer vision, image processing, machine learning, spatial statistics, or map-based data fusion. Experience
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using LC-HRMS to identify known and previously unknown substances in selected soil matrices; iii) assessing spatial patterns, persistence and transformation of contaminants where suitable data and samples
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UiO/Anders Lien 4th October 2026 Languages English English English 3-years PhD position in probabilistic machine learning and statistics Apply for this job See advertisement About the position We
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Engineering, Bioinformatics, Statistics, Applied Mathematics, Physics, or a closely related STEM field. Demonstrated experience developing AI and machine learning models for biomedical applications. Job
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key research questions that crosscut the themes of statistics, graphical models, causal inference, active learning, spatial modeling, and deep generative models. Execute multiple projects that will
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Associate I, Immunobiology Posting Number req26998 Department Immunobiology Department Website Link https://immunobiology.arizona.edu/ Location Tucson Campus Address 1501 N. Campbell Ave., Tucson, AZ 85719
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advanced biostatistics Computer proficiency, including use of statistical software for spatial analyses, such as ArcGIS, QGIS, R, Google Earth Engine Experience assembling, organizing, and analysing large
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spatial analysis of strandings data, including trend and time-series analysis. 6. Produce descriptive statistics, tables, figures and distribution maps, together with the analytical and interpretive content
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with an interest in developing novel methodology that complements our strengths in spatial and spate-temporal statistics, AI, and data science with substantive application interests (e.g., precision