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accuracy in link-tracing designs (e.g. Respondent driven sampling) Partial graph data collection strategies for networks (e.g. Aggregated Relational Data) Large scale models for anomaly detection on graphs
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
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employ advanced analytical methods in large databases, which include claims data and electronic health record data in conventional structures and in common data models. Our research group prioritizes a
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 1 month ago
of executive control, and contextual modulators of executive control like emotion and motivation. We use and develop advanced computational methods, including “big data” statistical methods, machine learning
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paradigms in primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science
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, leadership, and data science. Special training for writing successful ERC Starting Grants as a ‘ticket’ to an outstanding academic career. Being part of a thriving academic and social community in Vienna, one
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review of past field campaigns, through interactions with project stakeholders) Participate in summer field work Conduct observationally based research into the urban boundary layer using “big data” (e.g
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biochemistry techniques in weed science is essential Ability to use R statistical program or python is required Expectation of experience in computational tools and unix for analyzing and visualizing large data
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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post-Doctoral Researcher Department: EHE
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required Working knowledge of all aspects of planning and deploying an AI project, including initial problem specification, data gathering and analysis, model creation, and implementation Strong