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of machine learning models. · Experience with statistical analysis, multivariate methods, or comparative and phylogenetic analyses. · Experience using high-performance computing (HPC), cloud computing
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computational immunology as part of the NIH/NIAID-funded Multiscale Immune System Modeling (MISM) Center. The postdoctoral associate will contribute to and participate in meetings, workshops, trainings
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of reproducible bioinformatics pipelines using workflow-management and containerization tools, or high-performance or cloud computing for large genomic datasets. Experience with single-cell RNA-seq analysis using
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experiments, and connect them into live experimental campaigns so that AI checks every candidate before it reaches the robot deployed on the Genesis American Science Cloud with the Materials Project as
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experience in cloud computing and utilizing data from the All of Us Research Program are particularly well-suited for this position. Outstanding U of A benefits include health, dental, vision, and life
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-time data acquisition and telemetry systems Familiarity with cloud computing platforms and edge deployment of ML models Experience with uncertainty quantification, sensitivity analysis, or robust
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causal inference, real-world evidence, multimodal data integration, or cloud/high-performance computing is a plus. The Postdoctoral Researcher will collaborate closely with biomedical informaticians
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platform. The successful candidate will (1) integrate heterogeneous sensors and onboard computing hardware; (2) develop methods for LiDAR-based simultaneous localization and mapping (SLAM), autonomous
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, maintaining, and documenting open-source software tools or R packages Experience with geospatial analysis, environmental databases, and cloud or high-performance computing workflows Demonstrated record of peer
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI