Description Post Doc Fellow position on foundation models for anomaly detection: Starting March 1, 2026: For a 1-year funded project on developing foundation models for anomaly detection; with a focus on studying generalization to real-world tasks; including but not limited to designing pretraining datasets, studying training dynamics, working on multi-task pretraining over a mixture of synthetic and realistic data priors. (The term may be renewed for another year, upon mutual interest.) The position must be in-person. Note that a written reference from your PhD advisor as well as from an external collaborator are requested. The position will remain open until filled. Qualifications Doctoral degree in Computer Science or related Application Instructions 1. Resume 2. Research Statement/Project Proposals 3. 2 Recommendation letters (1 advisor, 1 external) Equal Employment Opportunity Statement Carnegie Mellon University is an equal opportunity employer. It does not discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex, disability, age, sexual orientation, gender identity, pregnancy or related condition, family status, marital status, parental status, religion, ancestry, veteran status, or genetic information. Furthermore, Carnegie Mellon University does not discriminate and is required not to discriminate in violation of federal, state, or local laws or executive orders.
Job Title
Post Doc Fellow - foundation models for anomaly detection