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optimize experimental protocols, analyze complex datasets, and contribute to scholarly publications. Emphasis is placed on artificial intelligence/machine learning approaches applied to digital data and
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técnicas de machine learning e IA. Sólidos conocimientos en análisis y tratamiento de datos, programación y desarrollo de modelos analíticos. Experiencia con bases de datos y herramientas de análisis
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LevelMaster Degree or equivalent Skills/Qualifications Solid background in Machine Learning and Deep Learning. Experience or interest in agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen, or similar
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of relevant research experience. Background conducting quantitative research in healthcare. Technical Skills or Knowledge: Proficiency in optimization, statistics, machine learning, econometrics, or AI
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a specific subject see General syllabus
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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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related to modeling and simulation of biological systems, 3) very good IT skills, in particular the ability to program in Python, 4) very good knowledge of machine learning methods, neural networks, and
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, including health and life insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu
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. Trains, deploys, and evaluates machine learning models. Uses subject matter and best practices knowledge to perform lab and/or research-related duties and tasks. Works independently to assist with