• Large-scale naturalistic image and video datasets (including curated "visual experience" style datasets; indoor/outdoor scenes, places, objects, and actions).

• Multimodal scene descriptions and embeddings: human and LLM-generated descriptions across multiple task prompts (e.g., affordances, navigation, aesthetics, danger, multisensory inferences), and embedding-based targets (e.g., MPNet/Transformer sentence encoders).

• Model-brain alignment using encoding/decoding with EEG time courses and/or fMRI (e.g., ridge regression, variance partitioning, RSA, representational geometry, temporal generalization).

• Computational measures of visual information (e.g., image statistics/compressibility proxies, deep network features, object/scene representations).

The postdoctoral fellow will lead and co-lead projects that combine computational modeling, machine learning, and EEG to answer questions about scene understanding and neural representation. The fellow will work closely with the PI, collaborate with students, and contribute to manuscripts, conference submissions, and grant-related research aims.

This is a 35-hour/week position with flexible scheduling; on-campus presence is encouraged for mentorship and collaboration, with hybrid arrangements possible depending on project needs. Barnard provides an intellectually vibrant environment with close ties to Columbia University and the broader NYC cognitive science community.

• Develop and maintain Python-based pipelines for large-scale data processing (images/video, text descriptions, embeddings, metadata).

• Train and evaluate models for representation learning and prediction (e.g., PyTorch, Transformers, CNN backbones, contrastive/embedding objectives).

• Perform rigorous statistical modeling of behavior and/or neural data.

• Conduct model-to-brain analyses for EEG (e.g., MNE-Python workflows; feature extraction; time-resolved encoding; representational similarity; temporal dynamics).

Open, Reproducible Science

• Write clean, documented code; use version control (Git); build reproducible experiments.

• Prepare datasets and analysis outputs for publication and sharing (data dictionaries, provenance, basic QA/QC).

Mentorship & Lab Citizenship

• Provide light-to-moderate mentorship to undergraduate/RA contributors (code review, research hygiene, analysis planning).

• Participate in lab meetings, research discussions, and departmental intellectual life.

Scholarly Output

• Lead/co-lead manuscripts and conference submissions (e.g., VSS/CCN), including figure generation and method writeups.

Please contact Dr. Michelle R. Greene at mgreene@barnard.edu with questions regarding the Postdoctoral Fellowship.

Salary: $68,000 - $72,000 annually

Barnard College is an Equal Opportunity Employer. Barnard does not discriminate due to race, color, creed, religion, sex, sexual orientation, gender and/or gender identity or expression, marital or parental status, national origin, ethnicity, citizenship status, veteran or military status, age, disability, or any other legally protected basis. Qualified candidates of all backgrounds are encouraged to apply for vacant positions at all levels.