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is required. Selected candidate may be asked to complete a pre-employment physical including a drug screen. Strongly Preferred Qualifications: Demonstrable experience with the R statistical computing
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of Utah Non‑Discrimination page . Online reports may be submitted at https://oeo.utah.edu https://publicsafety.utah.edu/safetyreport/ This report includes statistics about criminal offenses, hate crimes
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, and interprets cancer surveillance, population, geographic, environmental, and health services catchment area data using appropriate data management, statistical, GIS, and other programming software
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Geography, Botany and Zoology) and as part of the E3 learning foundry which includes the School of Natural Sciences, the School of Engineering and the School of Computer Sciences and Statistics. Even for
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spatial data visualization tools. Building AI solutions, including chatbots, RAG, and other LLM-based tools. Interest in and experience developing software to support data-driven research. Application
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Forecasting the Future of Biodiversity: Cutting-Edge Approaches to Population and Community Dynamics
: How do microbiomes vary, and what does that mean for host health and fitness? 3) Landscape-Level Change: What drives spatial variation in population dynamics across ecosystems? 4) Next-Gen Monitoring
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learning, AI, or statistical modeling applied to biological data Experience with genomics, transcriptomics, single-cell and/or spatial omics technologies Proficiency in scientific computing frameworks Strong
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at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics. Candidates with a strong background in the development of novel models and original