Qualifications
We invite applications from candidates at all ranks and career stages, with particular interest in candidates at the Associate or Full Professor level. Candidates should have completed, or be nearing completion of, a Ph.D. in Accounting or a related discipline. We seek scholars with strong theoretical, quantitative, and/or computational backgrounds—particularly those whose research leverages tools from artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and related methodologies. Applicants should demonstrate an established record of, or strong potential for, excellence in both research and teaching. Teaching responsibilities may include courses at the undergraduate, MBA, MSBA, and Ph.D. levels.
The Accounting group at the Tepper School is interdisciplinary and collaborative. Our strengths lie in the interface of accounting, economics, and data analytics. Methodologically, we place a strong emphasis on applied theory/empirical/experimental research grounded in accounting, economic, and/or computational theories. Examples of research by current faculty include economic consequences of climate reporting, cognitive biases in processing financial reports, tax evasion and income inequality, performance pay in knowledge creation, the role of accounting in banking regulations, and AI-assisted anomaly detection of accounting records.
We are at the frontier of accounting research aiming to address changing business needs due to rapid advancements in technology and the ubiquity of data by leveraging novel research approaches. The Accounting group at the Tepper School is ideally positioned to drive this innovation—bolstered by the recent establishment of the Accounting AI Research Lab and a strong track record of interdisciplinary collaboration with Carnegie Mellon faculty in economics, finance, statistics, machine learning, and computer science.
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