Postdoctoral Research Fellow, Cognitive/Computational Neuroscience
If you are a current Barnard College employee, please use the internal career site to apply for this position. Job: Postdoctoral Research Fellow, Cognitive/Computational Neuroscience The Barnard Visual Cognition Lab in the Department of Psychology at Barnard College is seeking applicants for one postdoctoral research fellow for the 2026–2027 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. We are especially excited about applicants who enjoy: (1) working with large, real-world datasets, (2) combining visual processing and semantic modeling, and (3) translating theory questions about perception and meaning into concrete, testable analyses. Proposed Start Date: 8/1/2026 (flexible within Summer/Fall 2026). 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). 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). 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: Research & Analysis 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 considered. Applicants 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 (1–2 pages) describing research interests, relevant technical experience (ML/statistics/neuro methods), and what you’d want to build/learn in this fellowship 1–2 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 before March 15, 2026. Interviews may early February, 2026. Applications will be considered until the position is filled. Please contact Dr. Michelle R. Greene at [email protected] 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. 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 College's good faith and reasonable estimate of the range of possible compensation at the time of posting. Company: Barnard College Time Type: Full time Barnard is an intellectually stimulating, diverse college community of approximately 800 full- and part-time faculty and staff dedicated to providing an extraordinary educational environment for our 2,600 students. Whether you are a current or potential Barnard employee, the Office of Human Resources is here to provide you with clear and accurate information and the best possible service. We hope that you find the site useful and will feel free to email any of the HR staff directly with questions or suggestions. We look forward to working with you.
Dirk Gütlin
Michelle Greene
