Research Software Engineer
Dartmouth College
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Job summary
Dartmouth College's Center for Open Neuroscience is seeking a Research Software Engineer to help build infrastructure that makes neuroscience data FAIR, open, and reproducible at scale. You will work on DataLad, DANDI, EMBER, and OpenNeuro Archives, contributing to open-source projects used by researchers worldwide.
The role focuses on designing workflows for versioned data management, applying them to real data wrangling tasks, and shaping standards for how neuroscience data is organized and
Qualifications
- Bachelor’s degree in CS, neuroscience or related field, or equivalent software contributions.
- 2 years of relevant software engineering and programming experience.
- Deep understanding of git and scripting around git plumbing.
- Proficiency in Python and its ecosystem (pytest, CLI).
- Experience with open source software development workflows and CI.
- Familiarity with virtualization/containerization (Docker/Podman, Singularity/Apptainer) and cloud platforms (AWS/GCP).
- Ability to work independently and communicate across distributed teams.
Responsibilities
- Design and implement workflows for versioned data management and processing.
- Apply workflows to real data wrangling tasks and contribute to national neuroimaging archives.
- Help shape standards for neuroscience data organization and sharing.
- Collaborate with developers, neuroscientists, and standards architects across institutions.
Skills
Education
Tools
Job description
Position Information
Posting date: 11/05/2026
Closing date: Open Until Filled
Position Number: 1129744
Position Title: Research Software Engineer
Hiring Range Minimum: $92,100
Hiring Range Maximum: $115,100
Union Type: Not a Union Position
SEIU Level: Not an SEIU Position
FLSA Status: Exempt
Employment Category: Regular Full Time
Scheduled Months per Year: 12
Scheduled Hours per Week: 40
Schedule: Monday - Friday, 8:00 am - 5:00 pm
Location of Position: Hanover, NH; Moore Hall, Room 430
Remote Work Eligibility? Onsite only
Is this a term position? No
Is this a grant funded position? Yes
The Research Software Engineer at the Center for Open Neuroscience ( CON ) helps build infrastructure that makes neuroscience data FAIR, open, and reproducible, working on open-source projects such as DataLad, DANDI, EMBER, and OpenNeuro Archives. Essential duties include designing and implementing workflows for versioned data management and processing, applying them to real data wrangling tasks, contributing to national neuroimaging data archives, and helping shape the standards for how neuroscience data is organized and shared. The role involves collaborating with developers, neuroscientists, and standards architects across institutions and countries.
The CON , part of the Department of Psychological and Brain Sciences at Dartmouth College, is seeking a Neuroinformagician - an enthusiastic Research Software Engineer to help build the infrastructure that makes neuroscience FAIR, Open, and Reproducible at scale. You will work on and with flagship open-source projects -including DataLad, ReproNim, DANDI, EMBER, and OpenNeuro Archives, and others - that are used by thousands of researchers worldwide and are central to the NIH BRAIN Initiative’s ecosystem.
This is a high-impact role at the intersection of scientific computing, data engineering, and open-source community building. You will design and implement workflows for versioned data management and processing, apply them to real data wrangling tasks, contribute to national neuroimaging data archives, and help shape the standards that define how neuroscience data is organized and shared. Your work will directly accelerate brain research across hundreds of laboratories.
You will collaborate with a diverse network of developers, neuroscientists, and standards architects across institutions and countries. The role offers genuine opportunities for professional growth - whether that means deepening expertise in distributed systems, learning neuroscience domain knowledge, contributing to published research, or developing leadership within open-source communities. Opportunities to present work and engage with collaborators at scientific conferences and developer sprints are available for those who enjoy them and have content to deliver!
Bachelors plus 2-3 years' experience or equivalent combination of education and experience
- Bachelor’s degree in computer science, neuroscience, or related field, or ability to demonstrate equivalent proficiency through a public track record of software engineering contributions (e.g., GitHub/GitLab profile).
- 2 years of relevant software engineering and programming experience.
- Deep understanding of git - comfortable with its internals and able to script around git plumbing, not just routine commit-and-push workflows.
- Solid proficiency in Python and its ecosystem: pytest, CLI frameworks, packaging.
- Experience with free and open source software development workflows: public code review, continuous integration, issue-driven development.
- Familiarity with virtualization/containerization (Docker/Podman, Singularity/Apptainer) and cloud platforms ( AWS, GCP, or similar).
- Ability to work independently, prioritize across multiple concurrent projects, and communicate effectively in a distributed team.
- Experience with git-annex or another data versioning system ( DVC, LFS ) for managing large files alongside code. Even better: demonstrated depth with git-annex, DataLad, or significant contributions to git’s ecosystem.
- Hands-on experience with neuroscience data and standards: familiarity with the Brain Imaging Data Structure (BIDS) and/or Neurodata Without Borders ( NWB ), including practical work with neuroimaging data (fMRI, EEG, MEG ) or neurophysiology recordings. Experience contributing to standards development is a strong plus.
- Demonstrable public history of open-source development — we will review your public GitHub/GitLab profile, commit history, and community interactions as part of the evaluation.
- Demonstrated efficiency with agentic AI systems for software development and beyond — e.g., using LLM-powered coding assistants, AI-driven code review, automated refactoring, or building AI-augmented workflows. We value candidates who thoughtfully integrate AI tools into their engineering practice to amplify productivity while maintaining code quality.
- Working knowledge of additional languages and platforms relevant to our stack: Rust, Haskell, JavaScript/TypeScript, shell scripting.
- Experience with high-performance computing environments and job schedulers: SLURM, HTCondor.
Jean Evans
Department Contact Phone Number
Jean.Evans@dartmouth.edu
Yaroslav Halchencko, Research Professor
Department Contact's Phone Number
yaroslav.o.halchenko@dartmouth.edu
Dartmouth College is an equal opportunity employer under federal law. We prohibit discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, veteran status, marital status, or any other legally protected status. Applications are welcome from all.
Employment in this position is contingent upon consent to and successful completion of a pre-employment background check, which may include a criminal background check, reference checks, verification of work history, conduct review, and verification of any required academic credentials, licenses, and/or certifications, with results acceptable to Dartmouth College. A criminal conviction will not automatically disqualify an applicant from employment. Background check information will be used in a confidential, non-discriminatory manner consistent with state and federal law.
This position is funded by a grant. Continuation is based upon available funds.
Smoking and the use of tobacco-based products (including smokeless tobacco) are prohibited in all facilities, grounds, vehicles or other areas owned, operated or occupied by Dartmouth College with no exceptions. For details, please see our policy. https://policies.dartmouth.edu/policy/tobacco-free-policy
Dartmouth is unable to provide visa sponsorship for this position.
https://searchjobs.dartmouth.edu/postings/87800
Design, implement, and maintain open-source software and standards for large-scale scientific data versioning, distribution, and archiving. This includes contributing to core tools (DataLad and git-annex ecosystem, DANDI CLI / API ), building and improving pipelines for ingesting and validating datasets against community standards (BIDS, NWB, HED), and developing containerized and cloud-native solutions for data processing and delivery. Work in the open on GitHub and other code hubs like hub.datalad.org using modern CI/CD practices, automated testing, and code review.
Percentage Of Time: 50%
Apply the tools and workflows you build to real-world datasets - organizing, validating, and curating neuroimaging and neurophysiology data from the Dartmouth Brain Imaging Center and public archives ( DANDI, OpenNeuro). This includes converting raw acquisitions into standards-compliant formats ( BIDS, NWB ), enhancing annotations (e.g. with HED ), troubleshooting data quality issues, and ensuring datasets are properly versioned and published. This hands-on work keeps development grounded in actual researcher needs and provides direct feedback into tool design.
Percentage Of Time: 25%
Collaborate with a distributed team of developers and researchers. Engage with the open-source and neuroscience communities through issue triage, code review, user support, and participation in standards development ( BIDS, NWB, HED, and related specifications). Demonstrate a commitment to diversity, inclusion, and cultural awareness through actions, interactions, and communications with others.
Percentage Of Time: 15%
Create and improve developer and user documentation for project components. Contribute to blog posts, tutorials, and scientific publications that communicate the impact and usage of the tools you build.
Percentage Of Time: 10%
* How many years of indirect experience do you have in related or transferable work that supports this role? Please briefly describe this indirect experience, including specific positions held and the number of years of indirect experience acquired while in these roles.
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