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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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data analysis and machine learning (e.g. XGBoost), including model interpretation techniques (e.g. SHAP). Very good oral and written proficiency in English. Excellent communication skills, ability
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and hardware security assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and
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Machine Learning within the School of Medicine at the University of Limerick. This is a methodologically focused PhD for candidates with strong quantitative backgrounds who wish to develop novel statistical
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specifically of both hedonic and causal machine learning methods for modelling housing market values and familiarity with appropriate data sources to support these. Skills Essential C1 Ability to communicate
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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CRC2 & Mitchell Funded Tenure-Track Faculty Positions in Supercomtuping and High-Performance Computi
Queen's University - Electrical and Computer Engineering, Smith Engineering | Kingston Downtown, Ontario | Canada | about 5 hours agoprovided by the Engineering Teaching and Learning Team, the Queen’s Centre for Teaching and Learning, the Department, and Smith Engineering. The Department of Electrical and Computer Engineering has 36 full
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technology management, or smart grids. Experience in development of mathematical meta-models, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno
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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. Position Description Advertised
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https