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Stanford University’s Department of Ophthalmology seeks software engineers to build and scale the Neuro-AI project infrastructure. You will ensure reproducibility, implement CI/CD, and maintain high-quality production code supporting interdisciplinary labs across Stanford, including Tolias and Moore labs.
You will develop applications, manage data workflows, and help advance brain-inspired AI research with robust, scalable software systems in a fast-paced academic setting.
The Department of Ophthalmology in the School of Medicine at Stanford University is launching an interdisciplinary Neuro-AI project dedicated to building a foundation model of the brain. This endeavor will involve multiple labs and faculty across the Stanford campus, including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute. Leveraging cutting-edge advances in electrophysiology and machine learning, this project aims to create a functional "digital twin" — a model that captures both the activity dynamics of the brain at cellular resolution and the intelligent behavior it generates, including perception, motor planning, learning, reasoning, and problem-solving.
This ambitious initiative promises to offer unprecedented insights into the brain's algorithms of perception and cognition while serving as a key resource for aligning artificial intelligence models with human-like neural representations. As part of this project, we are seeking talented software developers/engineers to support the whole team by developing and scaling the systems that allow our scientists to iterate quickly. In this role, you will play a critical role in ensuring the reproducibility and production-readiness of our codebase, as well as implementing Continuous Integration and Continuous Deployment (CI/CD) processes for all teams involved in the project. Your work will be essential in maintaining the highest standards of software quality, reliability, and efficiency.
This position promises a vibrant and cooperative atmosphere within the laboratories of Andreas Tolias (https://toliaslab.org), Tirin Moore (https://www.moorelabstanford.com) and other labs at Stanford University renowned for their expertise in perception, cognition, pioneering neural recording techniques, computational neuroscience, machine learning, and Neuro-AI research.