Data Engineer🔍School of Medicine, Stanford, California, United States📁Academic📅Aug 26, 2024 Post Date📅104384 Requisition #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 data engineers with extensive experience in data infrastructure engineering. The team will be responsible for designing, building, and operating the data pipeline infrastructure, which includes the entire flow of data from neurophysiological data acquisition to storage, processing, and preparation for large-scale training of foundation models. Ideal candidates will have practical experience in designing and scaling big data pipelines with proficiency in big-data storage architectures (data lakehouse) and relevant software tools and frameworks including but not limited to Delta Lake, Apache Spark, Apache Parquet, and Apache AirFlow.
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.Role & Responsibilities:* Work in a team of engineers and scientists to design, build, and maintain large scale data pipelines.* Set up and maintain the hardware and software infrastructure to support distributed computation, data orchestration, and fast-throughput distributed storage capable of supporting PB of data.* Coordinate with experimentalists, research scientists, and machine learning engineers to accelerate and facilitate the workflows for large-scale neuroscientific data analyses and foundation model training.
Stanford University |
Stanford University |
Stanford University |