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Neuroscience Research Methodologist
Job in
Cambridge, Middlesex County, Massachusetts, 02138, USA
Listed on 2026-06-01
Listing for:
Massachusetts Institute of Technology
Full Time
position Listed on 2026-06-01
Job specializations:
-
Research/Development
Data Scientist -
IT/Tech
Data Scientist
Job Description & How to Apply Below
PhD in Neuroscience or a related field; 3-5 years postdoctoral experience; demonstrated practical experience with data standards and repositories; sufficient computational proficiency to read, run, debug, and evaluate code fromneuroscience labs (Python and/or MATLAB required; experience with shell scripting and version control expected); familiarity with AI/ML tools applicable to research workflows, including experience using LLMs for code generation, documentation, or data processing tasks;
strong communication skills, with a demonstrated ability to explain technical concepts to researchers with diverse computational and scientific backgrounds. PREFERRED:
Experience across multipleneuroscience data modalities (e.g., fMRI, electrophysiology, single-cell genomics, calcium imaging, behavioral video); experience with containerization tools and/or workflow managers; practical experience deploying automated FAIR compliance tools, metadataextraction pipelines, or AI-assisted curation workflows; prior experience in a consulting or staff scientist capacity serving multiple research groups; familiarity with the BRAIN Initiative data infrastructure landscape (DANDI, BICAN, or related consortia).
5/15/2026
NEUROSCIENCE RESEARCH METHODOLOGIST, Brain and Cognitive Sciences, will be responsible for open science practices and data management across all the areas of molecular/cellular, systems, cognitive, and computational neuroscience. This role will work directly with individual BCS labs to assess current data management practices, recommend solutions, and provide technical support for implementing data standards, FAIR-compliant workflows, and AI-assisted tools for data organization and curation.
The full description is available here:
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