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public health. In this role, you will develop and evaluate novel AI and machine learning methods using large-scale multimodal datasets, contributing to epidemiology-informed foundation models, predictive
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extreme weather forecasting, employing data science models as developed in computer vision and natural language processing (NLP). This project leverages the large-scale high-performance computing (HPC
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systems routinely handle data rates of several GB/s and support large-scale scientific data workflows. To support sustainable data management at next-generation photon science facilities, we are seeking a
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skills and strong publication records to apply. Some skills in analyzing/evaluating large data sets are highly desirable. Knowledge of an advanced programming language such as MATLAB, Python, etc. is
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cultural activities; and more! The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services
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spatial transcriptomic data. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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consortium connects AI model development directly to large-scale microbiome data generation, microbial culture collections, greenhouse experiments and field validation. More information For more information
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Respirator (PAPR) and other necessary PPE for up to 4 hours at a time. Ability to lift up to 40 lbs. Work with large animals or wildlife. Additional Information: Minimum Qualifications: PhD in Molecular
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are software representations of physical assets, processes, or systems. They leverage real-time data to mirror the behaviour and characteristics of their physical counterparts, enabling predictive maintenance