Systems Engineer (Research and Development Scientist & Engineer 2, 2-year fixed term) - Stanford University

Systems Engineer (Research and Development Scientist & Engineer 2, 2-year fixed term)

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 Systems Engineers with an extensive background in implementing and maintaining experimental setups used to run large-scale neuroscience experiments. Ideal candidates will have several years of practical experience in building and running multi-modal experimental setups, including implementation of state-machines, the synchronization of different data modalities (such as visual stimulation with eye tracking), and large-scale electrophysiology techniques. Additionally, candidates should exhibit a strong background in quantitative fields such as Mathematics, Physics, Engineering, or Computer Science.

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 together with a team dedicated to developing novel stimulus and behavioral paradigms, as well as large-scale Neuropixels recordings, for experiments in head-fixed behaving animal species beyond current state-of-the-art methods.
• Build and maintain multi-modal experimental setups, including integration of hardware components (e.g. eye/face/body cameras, widefield stereo displays, binocular eye trackers, head-stages for electrophysiology, high precision timing, photodiodes and relays) and software components (e.g. LabVIEW, OpenEphys, Kilosort), the latter in collaboration with Software Engineers.
• Work together with other teams of the Enigma Project to ensure efficient, large-scale, industry-level quality of experiments.

* - Other duties may also be assigned

DESIRED QUALIFICATIONS:

• PhD, Master’s or Bachelor’s degree in Electrical Engineering, or a related field.
• 2-3 years of practical experience in building and running experimental neuro-behavioral and/or neuro-physiological paradigms.
• Expertise in implementing hardware and software components for such experiments including concepts of state-machines, real-time high throughput data acquisition and storage, signal processing, visual stimulus presentation, and high resolution eye tracking.
• Proficiency in LabVIEW, Matlab, and Python.
• Experience with National Instrument hardware.
• Experience with designing databases in Python/MySQL for big data.
• Experience with problem-solving and engineering solutions for large-scale experiments in neuroscience.
• Experience with networking and cloud storage.

EDUCATION & EXPERIENCE (REQUIRED):

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

KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):

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

· Demonstrated project leadership experience.

· Demonstrated experience leading and/or managing technical professionals.

CERTIFICATIONS & LICENSES:

None

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.

The expected pay range for this position is $156,560 to $180,039 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.

At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website (https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.

School of Medicine, Stanford, California, United States