Research Assistant Professor - Software Engineering

Position Responsibilities

Lead the adoption of software engineering best practices for the cluster's research software development, including Agile project management (e.g., Scrum or Kanban), code review, automated testing, continuous integration, and release management.
Architect and develop software components of the rat-to-atlas mapping pipeline, including data ingestion, processing, and visualization tools.
Develop the Brain Maps 4.0 and Chemopleth 1.0 software toward robust public releases, building on existing prototypes with latitude to refactor or rebuild as engineering judgment requires, and ensuring interoperability with international neuroinformatics infrastructure such as EBRAINS and with Python-based community tooling such as the BrainGlobe Atlas API.
Collaborate with cluster-hire colleagues in behavioral neuroscience, circuit imaging and mapping, and ML/AI to translate research requirements into reliable software and to support multi-modal data integration and atlas development.
Contribute to peer-reviewed publications and federal grant applications describing the cluster's software, data, and infrastructure outputs, including the open-access digital atlas of brain reward circuits.
Mentor graduate and undergraduate trainees to contribute their efforts to the research pipeline.

Job Requirements

• Ph.D. in computer science, software engineering, biomedical informatics, computational science, or a related field; or a Master's degree with substantial professional research software engineering experience.
• Experience with software engineering best practices, including Agile project management (e.g., Scrum or Kanban), version control, automated testing, code review, and documentation.
• Demonstrated experience designing and shipping non-trivial scientific or research software, evidenced by repositories, releases, or production deployments.
• Proficiency in Python and at least one additional language relevant to scientific computing or web infrastructure.
• Experience mentoring or training undergraduate or graduate students in software engineering practice, including supervision of student software projects.
• Demonstrated interest in or experience with neuroscience, biomedical imaging, or related scientific domains.
• Demonstrated ability to work in interdisciplinary teams that translate scientific and experimental requirements into reliable software.

Preferred Qualifications

• Experience working in academic or research-intensive environments, including open-source scientific projects.
• Familiarity with neuroscience or biomedical data formats and standards.
• Track record of independent grant submissions or co-authored funded proposals related to research software, infrastructure, or scientific computing.
• Experience with web-based scientific applications, data visualization, or large-image rendering.
• Experience with containerization (e.g., Docker) and cloud or HPC deployment of scientific software.
• Engagement with FAIR data principles and shared neuroscience infrastructure (e.g., EBRAINS, NIH BRAIN Initiative resources).