Postdoctoral Position in AI, NLP, and Machine Learning for Invoice Anomaly Detection

Toronto Metropolitan University is seeking a postdoctoral researcher to join the Internet of Things Analytics (IoTA) Laboratory, led by Associate Professor Rasha Kashef. The project centers on developing AI-native models for detecting invoice anomalies and mitigating vendor overspending prior to payment approvals. The research will integrate advanced natural language processing (NLP) techniques, machine learning (ML) models, and document intelligence technologies to create a robust solution capable of parsing complex invoices, analyzing contractual agreements, and detecting potential anomalies in real time. This opportunity is open exclusively to domestic candidates (Canadian citizens or permanent residents). The ideal applicant will have a PhD in Computer Science, Information Technology, or a closely related field, with demonstrated expertise in AI, NLP, and ML. Experience with document intelligence and real-time anomaly detection is highly desirable. The successful candidate will work in a collaborative research environment at Toronto Metropolitan University, contributing to innovative solutions in the intersection of artificial intelligence and business process automation. Interested candidates should contact Associate Professor Rasha Kashef directly via LinkedIn and submit their CV for consideration. This position offers the chance to work on cutting-edge research with real-world impact in the field of document analysis and financial technology.