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Field
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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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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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cuantitativo. Capacidad para trabajar con grandes conjuntos de datos y entornos computacionales. / Experience in data science, data management and optimization, and machine learning and AI techniques. Strong
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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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machine-learning methods using experimental data provided by collaborating experimentalists. A central part of the work will be to identify and define the most relevant parameters governing material growth
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. Work on other ATLAS physics topics may also be considered depending on the candidate’s expertise. A PhD in particle physics and substantial experience in data analysis are required. Additional valuable
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-augmented generation (RAG) approaches Systems and mathematical modeling of biological or complex systems Natural language processing and machine learning Data harmonization and integration Record of research
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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University safety requirements. Machines and Equipment: Operational knowledge of laboratory equipment for mechanical testing of concrete materials Operational knowledge of equipment for 3D Printing of concrete
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collection, data organization, and project execution to publication. Other Duties Other duties as assigned. Additional Information Machines or equipment used in the performance of essential duties Computer