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Job:
Postdoctoral Research Fellow Cognitive/Computational NeuroscienceThe Barnard Visual Cognition Lab in the Department of Psychology at Barnard College is seeking applicants for one postdoctoral research fellow for the academic year. This is a one-year full-time position with a possibility of renewal contingent on funding and performance. The fellowship is designed for an emerging scholar who wants deep hands-on experience working at the intersections of human cognitive science and artificial intelligence to understand the time-course of naturalistic scene understanding.Job Description:
The Visual Cognition Lab studies how humans perceive interpret and navigate real-world scenes linking visual information semantic inference and task demands to behavior and brain activity. Ongoing projects include:
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).
Modelbrain 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).
Position Summary
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.
Responsibilities Include:
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.
Skills Qualifications & Requirements:
Required Qualifications
PhD by start date in Psychology Neuroscience Cognitive Science Computer Science Statistics or a related field.
Strong scientific computing skills in Python (NumPy/Pandas reproducible pipelines).
Demonstrated ability to run and interpret statistical analyses with appropriate validation (cross-validation uncertainty robustness checks).
Evidence of research productivity (publications/preprints conference papers or equivalent).
Commitment to inclusive mentorship and working respectfully in a diverse academic community.
Preferred (not all required)
Experience with machine learning / deep learning (PyTorch; model training; GPU workflows).
Experience with Transformers / text embeddings / multimodal modeling (e.g. Hugging Face ecosystem).
Experience with EEG (MNE-Python) and encoding/decoding frameworks.
Comfort working with large datasets.
Strong data visualization and figure generation skills for publication.
Application Requirements
Only complete applications submitted via Workday will be are required to upload the following documents:
Curriculum Vitae (maximum file size: 5 MB)
A single PDF file (maximum file size: 30 MB) containing:
Cover letter (12 pages) describing research interests relevant technical experience (ML/statistics/neuro methods) and what youd want to build/learn in this fellowship
12 representative artifacts (optional but encouraged): a preprint/paper GitHub repo or a short code sample.
Finalists will be asked to identify three references (at least one from a primary research supervisor/PI) who will be contacted at a later stage.
Priority will be given to applications received beforeMarch 15 2026. Interviews may earlyFebruary 2026. Applications will be considered until the position is filled.
Please contact Dr. Michelle R. Greene atwith questions regarding the Postdoctoral Fellowship.
Salary:$68000 - $72000 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.
The salary of the finalist selected for this role will be set based on a variety of factors including but not limited to departmental budgets qualifications experience education licenses specialty and training. The above hiring range represents the Colleges good faith and reasonable estimateof the range of possible compensation at the time of posting.
Company:
Barnard CollegeTime Type:
Full time