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background and relevant professional experience – 40% Evaluation of academic performance and/or relevant professional experience in machine learning, software engineering, or cybersecurity. Experience in
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a wide array of family-friendly and cultural programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/ Equal Opportunity Employer: Duke is an Equal Opportunity Employer
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profile and an interest in developing new AI models for high-dimensional biological data. You should have a solid foundation in areas such as machine learning, applied mathematics, statistics
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, learning how we think about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets. At Jane Street, our researchers, engineers, and
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of campus and community resources; knowledge of disability models and theories and inclusive educational design; demonstrated presentation skills; working knowledge of common computer applications (e.g. word
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-making systems. Develop Advanced ML/AI Models for Air Quality Applications Applies machine learning (ML) and artificial intelligence (AI) techniques to enhance traditional chemical transport modeling
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with the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The research group on statistical models
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for vehicle applications; Abilities in using Finite Element modeling and analysis; Knowledge of injury biomechanics; Knowledge of Artificial Intelligent (AL) and Machine Learning (ML) techniques; and Abilities
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individuals and patients. These projects involve large-scale neuroimaging data collection at 3T and 7T, computational modeling of brain responses using machine learning methods, and cross-institutional clinical
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights