Research Scientist, Neurology AI and Brain Data Science (24-Month Fixed-Term)

Stanford Reglab; United States; On-site; USD 140,000 - 200,000; Full time

Job summary

The Department of Neurology & Neurological Sciences at Stanford University School of Medicine is advancing AI‑driven brain health research, deploying models that interpret EEG, polysomnography, wearables, imaging, and linked electronic health records.

We seek a Research and Development Scientist and Engineer 2 to lead scientific work, frame research questions, design studies, develop and validate models, publish results, and guide postdocs toward clinical deployment in a hybrid

Qualifications

• PhD preferred in biomedical informatics, computer science, electrical/biomedical engineering, neuroscience, statistics, epidemiology, or related field.
• Five+ years of research experience with independent leadership of projects.
• Strong record of peer‑reviewed publications applying ML or advanced statistics to biomedical data.
• Deep expertise in ML/DL for time-series or signal data; Python and PyTorch proficiency.
• Experience with EEG, polysomnography, or other neurophysiological data preferred.
• Experience with large-scale electronic health record data, causal inference, or clinical model development/validation.
• Contributions to grant proposals; named investigator experience desirable.
• Mentoring or supervising junior scientists or engineers.
• Familiarity with translational/regulatory pathways for clinical AI desirable.
• Excellent scientific writing and cross‑functional collaboration skills.

Responsibilities

• Lead scientific work across the program: framing questions, designing studies, developing and validating models, and publishing results.
• Guide models from prototype to rigorous validation toward clinical deployment.
• Provide scientific direction to postdocs and students; contribute to grant proposals.
• Help shape the research agenda of the Stanford Neurology AI Center.

Skills

Machine learning for time-series

Python & PyTorch

Mentoring or supervising

Scientific writing & presentation

Translational/clinical AI knowledge

Grant proposal experience

Cross-disciplinary collaboration

Experience with EEG/neurophysiology

Five+ years research leadership

Education

PhD in relevant field

Master's degree with research experience

Bachelor’s degree with experience

Job description

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 2 to serve as a senior research scientist leading scientific work across this program. Where our engineering staff build the infrastructure, you will drive the science: framing the questions, designing the studies, developing and validating the models, and publishing the results. You will work with one of the largest curated collections of clinical neurophysiology data assembled anywhere, spanning EEG, polysomnography, wearable monitoring, imaging, and linked electronic health records.

The role is deliberately broad. You will lead your own lines of investigation, guide models from prototype through rigorous validation toward clinical deployment, provide scientific direction to postdoctoral fellows and students, contribute to grant proposals, and help shape the research agenda of the emerging Stanford Neurology AI Center.

This position is offered as a hybrid role (on-site at Stanford’s main campus, Center for Academic Medicine – 453 Quarry Rd., three days per week and telecommuting two days per week), subject to operational needs.

DESIRED QUALIFICATIONS

• PhD preferred, in biomedical informatics, computer science, electrical or biomedical engineering, neuroscience, statistics, epidemiology, or a related field.
• Master's degree with commensurate research experience will be considered.
• Five or more years of relevant research experience, including independent leadership of research projects from question formulation through publication.
• Strong record of peer-reviewed publications applying machine learning or advanced statistical methods to biomedical, physiological, or clinical data.
• Deep expertise in machine learning and deep learning for time-series or signal data; strong proficiency in Python and modern frameworks such as PyTorch.
• Experience with EEG, polysomnography, or other neurophysiological data strongly preferred.
• Experience with large-scale electronic health record data, causal inference, or development and external validation of clinical prediction models.
• Demonstrated experience contributing to competitive grant proposals; prior success as a named investigator desirable.
• Experience mentoring or supervising junior scientists, students, or engineers.
• Working knowledge of translational and regulatory pathways for clinical AI (e.g., FDA Software as a Medical Device) desirable.
• Excellent scientific writing and presentation skills, and the ability to work effectively across clinical, engineering, and data science teams.

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, http://adminguide.stanford.edu.

Design, develop, execute and implement specialized equipment or instruments, or systems for a research science and engineering projects. May oversee technicians, collaborate with other engineers and researchers, coordinate interdisciplinary activities and research efforts, and contribute to scientific literature and conferences.

Core Duties

• Provide leadership and scientific expertise in the planning and implementation of major projects, services, facilities, and activities.

• Develop advanced technological ideas, and guide their development into a final product or new approaches to research. Carry out complex or unique assignments important to the advancement of the field.

• Provide expert consultation and collaboration regarding technical requirements, capabilities, and advancement opportunities; make substantive contributions in diverse technical areas.

• Provide technical direction to other research staff, engineering associates, technicians, and/or students; facilitate workshops and demonstrations on research methods; educate and train users on research methodology and effective tools and techniques.

• Contribute to or co-author published articles, presentations, or scientific papers; identify research and development funding opportunities.

• Supervise staff and resources to meet program objectives.

Minimum Education and Experience

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

Knowledge, Skills and Abilities

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

• Demonstrated project leadership experience.

• Demonstrated experience leading and/or managing technical professionals.