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of data to solve problems and find answers. Applying statistical learning and data mining techniques to deliver concrete business outcomes. Contributing to rapid data‑driven storytelling that helps leaders
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of research interest and function are: IT and the environment, water, responsible mining, sustainable energy, climate solutions, disaster resilience, and so forth. ACE boasts multiple, simultaneous projects
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teaching-track faculty and 56 tenured and tenure-track faculty with wide-ranging research interests, and strong research groups in cybersecurity, systems and networks, machine learning and data mining
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including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources 15% Identifies and implements or guides others in implementing appropriate data science
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of postdoctoral associates, PhD students, and several Master’s or undergraduate students across multiple universities and organizations. The research team will work alongside the engineering team to investigate
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interpret graduate data by accessing institutional systems including Aurora, Pegasus Mine Portal, GradInfo, and PeopleSoft. Regularly monitor active student enrollment, candidacy progression, academic
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Computer Science, Computer Engineering, or Electrical Engineering or related fields by July 1, 2025. A strong commitment to excellence in research and teaching with potential for developing robust externally funded
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including, but not limited to, data mining, descriptive statistics, and data visualization. The ability to learn new approaches and techniques as the need arises. Teaching or TA experience at the college
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such as the binomial distribution), and data analysis including, but not limited to, data mining, descriptive statistics, multivariate modelling, and data visualization. Proficiency with permutation testing
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PhD: 3-4 years full-time; 6-8 years part-time; Thesis of Max 80,000 words Apply now Research projects Research projects Self-funded projects Indicative Data Science: Extracting 3D Models of Cities