Mechatronics and Robotics Engineering Associate

Stanford University School of Medicine; Palo Alto (CA); On-site; USD 133,000 - 158,000; Full time

Job summary

Stanford University School of Medicine seeks an Engineer Associate to develop next‑gen robotic hardware and intracortical brain‑interfacing tech. You will prototype lightweight, scalable neural interfaces and robotic systems enabling interactions in virtual environments.

Embedded within a multidisciplinary team led by Andreas Tolias, this role blends neuroscience, engineering, software, and AI to advance Neuro‑AI frontiers and experimental capabilities.

Qualifications

• Bachelor’s degree in engineering, science, or related field and six years of relevant experience.
• Experience designing robotic systems, especially haptic interfaces or surgical robotics.
• Proficiency with CAD tools and rapid prototyping.

Responsibilities

• Develop backdrivable robotic manipulanda for physical interactions in virtual environments.
• Create modular neural recording and animal behavior systems; automate assembly processes.
• Design and integrate miniaturized actuation and control, including piezoelectric motors.
• Maintain design libraries and documentation for versioning and collaboration.
• Collaborate with systems engineers and researchers to solve evolving experimental needs.

Skills

Robotics design

Mechatronics

CAD engineering

Embedded vision

Control systems

3D printing

Neuroengineering interest

Education

Bachelor’s degree in engineering, science, or related field

Tools

OnShape

SolidWorks

Fusion 360

Job description

Job Description

We are seeking an Engineer Associate with strong mechanical engineering and mechatronic design skills to develop next generation robotic hardware and intracortical brain-interfacing technology. Our team is working to understand the neuroscience of intelligence, and mechatronic systems are critical to the depth and scale of our experimental ambitions. The ideal candidate will play an essential role in developing unique robotic systems that enable physical interactions within virtual environments. They will also prototype mechatronic microassembly processes that facilitate lightweight, highly scalable, precisely controlled neural interfaces, enabling the team to record neural activity and understand the brain at unprecedented scale.

Job Description

We are seeking an Engineer Associate with strong mechanical engineering and mechatronic design skills to develop next generation robotic hardware and intracortical brain-interfacing technology. Our team is working to understand the neuroscience of intelligence, and mechatronic systems are critical to the depth and scale of our experimental ambitions. The ideal candidate will play an essential role in developing unique robotic systems that enable physical interactions within virtual environments. They will also prototype mechatronic microassembly processes that facilitate lightweight, highly scalable, precisely controlled neural interfaces, enabling the team to record neural activity and understand the brain at unprecedented scale.

This role is ideal for individuals who thrive at the rapidly evolving interface of neuroscience, engineering, software development, and artificial intelligence, and want to contribute to a uniquely interdisciplinary effort. This position is embedded within a vibrant team of neuroscientists, engineers, and software developers led by Andreas Tolias ( toliaslab.org ) and collaborators.

Role & Responsibilities

• Develop backdrivable robotic manipulanda that enable physical interactions (grasping, object manipulation, and pick and place) within software-defined virtual environments
• Develop modular systems for neural recordings and animal behavior experiments, as well as scalable approaches to automate assembly of these systems
• Design or integrate new approaches to miniaturized linear actuation and control, e.g., via piezoelectric motors, and online monitoring systems, e.g. via embedded cell-phone cameras and real-time, closed-loop computer vision software.
• Maintain design libraries and documentation for versioning, reproducibility, and team collaboration
• Collaborate closely with systems engineers and researchers to find creative solutions to evolving experimental needs

Qualifications

DESIRED QUALIFICATIONS:

• Demonstrated prior experience designing and implementing robotic systems, especially haptic interfaces or surgical robotics
• Prior experience with microassembly systems, especially high-precision robot arms, linear actuation, precision force sensing, rapid calibration
• Strong experience with CAD tools (e.g., OnShape, SolidWorks, Fusion)
• Strong familiarity with electronic circuits, motor control, embedded cameras, PCB design, rapid prototyping, microcontroller programming and integration, simulation / testing, and LEDs
• Strong experience with software development, preferably spanning microcontroller programming, control systems, computer vision, VR environments, 3d rendering, etc.
• Experience with rapid prototyping using 3D printers
• Interest in programmatic CAD design, computational geometry, and/or CAD simulation
• Hands-on experience in a machine shop or prototyping lab
• Practical understanding of fabrication tolerances, material selection, and mechanical fabrication
• Ability to work flexibly and collaboratively across multiple concurrent projects in a fast-paced, interdisciplinary environment
• An interest in advancing the frontier of Neuro-AI. Neuroscience and bioengineering background not required.

Required

EDUCATION & EXPERIENCE (REQUIRED):

Bachelor’s degree in engineering, science, or related field and six years of relevant experience; or a combination of education and relevant experience.

Knowledge, Skills And Abilities (required)

• Demonstrated knowledge and skills of advanced scientific or engineering principles and practices.
• Extensive experience applying complex scientific and engineering principles and performing special technical services and the ability to articulate and translate implementation requirements to the planning, design, development, operations, and performance of complex equipment and systems
• In-depth experience using software applications, systems, or programs relevant for the job.
• Ability to supervise others in oversight and management of instrumentation or system installation.
• Demonstrated ability to oversee, maintain, and develop a laboratory space including demonstrated ability to and supervise the work of technicians and other staff associated with the group.
• Demonstrated ability to critically review research proposals, evaluate research capabilities, and make recommendations.
• Demonstrated ability to establish, communicate, and enforce compliance with health and safety policies and procedures.
• Demonstrated ability to effectively supervise and train a diverse work staff.

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.

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 $132,996 to $157,641 per annum.

Stanford University provides pay ranges representing its good faith estimate of the salary or hourly wage the university reasonably expects to pay for a position upon hire. 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.