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Research Software Engineer

Job in Hanover, Grafton County, New Hampshire, 03755, USA
Listing for: Dartmouth College
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    Data Security, Cybersecurity
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Research Software Engineer.

The Center for Open Neuroscience (CON) ((Use the "Apply for this Job" box below).), part of the Department of Psychological and Brain Sciences at Dartmouth College, is seeking a Neuroinformagician—a Research Software Engineer to build the infrastructure that makes neuroscience FAIR, Open, and Reproducible  will work on flagship open‑source projects—including Data Lad, DANDI, EMBER, and Open Neuro Archives—that are used by thousands of researchers worldwide and are central to the NIH BRAIN Initiative’s ecosystem.

This high‑impact role lies 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, contribute to national neuroimaging data archives, and help shape the standards that govern how neuroscience data is organized and shared. Your work will accelerate brain research across hundreds of laboratories and offer opportunities for professional growth, conference presentations, and leadership in open‑source communities.

Required Qualifications
  • Bachelor’s degree in computer science, neuroscience, or a related field, or an equivalent combination of education and experience demonstrated through a public track record of software engineering contributions.
  • Minimum of 2 years of relevant software engineering and programming experience.
  • Deep understanding of Git, comfortable with its internals and able to script around git plumbing rather than 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.
Preferred Qualifications
  • Experience with git‑annex or another data‑versioning system (DVC, LFS) for managing large files alongside code. Demonstrated depth with git‑annex, Data Lad, 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), 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—review of Git Hub/Git Lab profile, commit history, and community interactions.
  • Demonstrated efficiency with AI‑powered coding assistants and AI‑augmented workflows.
  • Knowledge of additional languages and platforms relevant to our stack:
    Rust, Haskell, JavaScript/Type Script, shell scripting.
  • Experience with high‑performance computing environments and job schedulers: SLURM, HTCondor.
Key Accountabilities Code Development and Maintenance
  • Design, implement, and maintain open‑source software and standards for large‑scale scientific data versioning, distribution, and archiving—including contributing to core tools (Data Lad and the git‑annex ecosystem, DANDI CLI/API), building and improving pipelines for ingesting and validating datasets against community standards (BIDS, NWB, HED), and developing containerised and cloud‑native solutions for data processing and delivery.
  • Work openly on Git Hub and other code hubs using modern CI/CD practices, automated testing, and code review.

Approximately 50% of the time is devoted to this account.

Data Wrangling and Curation
  • Apply the tools and workflows you build to real‑world datasets—organising, validating, and curating neuroimaging and neurophysiology data from the Dartmouth Brain Imaging Center and public archives (DANDI, Open Neuro). 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.

Approximately 25% of the time is devoted to this account.

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