Research Software Engineer, Brain Data Science Platform (24-Month Fixed-Term)

The Department of Neurology & Neurological Sciences at Stanford University School of Medicine is building a world-class program at the intersection of artificial intelligence and brain health. The laboratory of Dr. M. Brandon Westover develops and deploys AI systems that interpret brain data at scale — EEG, sleep studies, wearable recordings, neuroimaging, and the electronic health record — to improve diagnosis and treatment in epilepsy, neurocritical care, sleep medicine, and neurology broadly.

We are seeking a Research and Development Scientist and Engineer 1 to serve as a core software engineer for the Sleep Health Data Science Platform, a major component of our Brain Data Science Platform. This is a hands-on engineering role at the center of a rapidly growing clinical research data ecosystem. You will build the pipelines that bring in EEG, polysomnography, wearable, imaging, and EHR data from Stanford and partner hospitals; make that data safe and usable through automated de-identification and standardization; and help build the AWS-based platform that turns it into a research resource for investigators across Stanford and beyond. You will also help move AI models out of the lab and into clinical use, with particular emphasis on AI-assisted EEG interpretation.

This role suits an engineer who wants to go deep on a domain. You will be expected to become a genuine expert in medical data — how it is generated, what it means clinically, and where it goes wrong — and to bring that expertise to bear on the architecture.

DESIRED QUALIFICATIONS:

• Master's degree or PhD preferred, in Computer Science, Biomedical Informatics, Electrical Engineering, Data Science, or a related technical field.
• Experience working with electronic health record (EHR) data strongly preferred, including extraction, structuring, and analysis of clinical data from systems such as Epic, and familiarity with clinical data warehouses.
• Three or more years building production data pipelines and backend services, with strong proficiency in Python.
• Experience with cloud infrastructure, preferably AWS (S3, Lambda, Batch/ECS, RDS, IAM), and with infrastructure-as-code.
• Experience with workflow orchestration (Airflow, Prefect, Nextflow, Snakemake, or similar), containerization (Docker), and version control and CI/CD (Git, GitHub Actions).
• Experience with healthcare data standards and formats — EDF/EDF+, DICOM, HL7/FHIR, OMOP/OHDSI — and with de-identification of protected health information.
• Experience working with large physiological time-series data (EEG, PSG, ECG, actigraphy, or wearable sensor streams) strongly preferred.
• Familiarity with HIPAA, IRB, and data use agreement requirements governing human subjects research data.
• Experience deploying machine learning models into production or clinical settings, including model serving, monitoring, and EHR integration, desirable.
• Demonstrated ability to work independently, scope ambiguous problems, and deliver reliable systems.
• Strong written and verbal communication skills, and genuine interest in becoming a domain expert in clinical neurophysiology and medical data.

PHYSICAL REQUIREMENTS*:

• Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds.
• Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully.
• Rarely kneel/crawl, climb (ladders, scaffolds, or other), reach/work above shoulders, use a telephone, writing by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects that weigh >40 pounds.

* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

WORKING CONDITIONS:

• May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB TWA, Allergens/Biohazards/Chemicals /Asbestos, confined spaces, working at heights ?10 feet, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather.
• May require travel.

WORK STANDARDS:

• Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
• Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
• Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, .
  

Core Duties:

• Design and develop complex and specialized equipment, instruments, or systems; coordinate detailed phases of work related to responsibility for part of a major project or for an entire project of moderate scope.

• Develop technical and methodological solutions to complex engineering/scientific problems requiring independent analytical thinking and advanced knowledge.

• Develop creative new or improved equipment, materials, technologies, processes, methods, or software important to the advancement of the field.

• Contribute technical expertise, and perform basic research and development in support of programs/projects; act as advisor/consultant in area of specialty.

• Contribute to portions of published articles or presentations; prepare and write reports; draft and prepare scientific papers.

• Provide technical direction to other research staff, engineering associates, technicians, and/or students, as needed.

Minimum Education and Experience

Bachelor’s degree and three years of relevant experience, or combination of education and relevant experience.

Knowledge, Skills and Abilities:

• Thorough knowledge of the principles of engineering and related natural sciences.

• Demonstrated project management experience.