Laboratory Automation Engineer (Robotics and Digital Twins)

Position Overview

The Laboratory Automation Engineer will program, integrate, and keep running the robots of the autonomous laboratory in Bethesda, starting with the BAB400, so that biological experiments run reliably without a person at the bench. The role builds the software layer that turns robot hardware into orchestrated, repeatable workflows, using the MADSci framework from Argonne National Laboratory. It also builds digital twins of the robots and workcells, used to plan, test, and validate protocols before they run on real hardware.

The position combines hands-on robotics work in a biological lab with production-quality software development, and it works closely with IDSS data engineers, bioinformaticians, and the biologists who define the protocols.

Key Responsibilities

Robot programming and control. Program, calibrate, and maintain the BAB400 and other laboratory robots, including arms, liquid handlers, plate movers, and incubator and imaging interfaces.

MADSci integration. Deploy MADSci modules, nodes, and workcell definitions so each robot and instrument can be commanded, monitored, and scheduled through a common interface. Contribute fixes and new modules back to the framework where appropriate.

Workflow development and scheduling. Translate biological protocols (cell culture, iPSC maintenance, passaging, media exchange, imaging, sampling) into automated workflows with sequencing, timing, resource tracking, and recovery from failures.

Instrument and data integration. Connect robot and instrument outputs to the data pipelines, LIMS, and metadata systems maintained by IDSS, so every run is logged, traceable, and reusable.

Validation and reliability. Develop acceptance tests, error handling, logging, and monitoring. Troubleshoot hardware and software faults, and document root causes and fixes.

Safety and compliance. Implement interlocks and safe-state behavior, and follow laboratory, biosafety, and NIH/HHS security requirements.

Tool evaluation. Evaluate robots, drivers, simulators, and frameworks, and prepare short technical assessments for IDSS leadership.

Training and documentation. Train laboratory staff to operate and recover the system, and write standard operating procedures and technical documentation.

Required Qualifications

The selection standard is demonstrated ability to get automated systems working. A degree in engineering, computer science, robotics, or a related science is common, but equivalent practical experience is fully acceptable.

Automation experience. Several years of hands-on experience with laboratory robotics or comparable automation, such as robotic arms, liquid handlers, plate handlers, or workcells, including installing, programming, calibrating, and troubleshooting them.

Robot software. Experience with the software that drives laboratory robots: vendor APIs and SDKs, device drivers, and orchestration or scheduling software.

Laboratory context. Some experience with robotics in a biological laboratory (cell culture, molecular biology, or assay automation), and comfort working around biological materials under biosafety practices.

Programming. Strong Python, including asynchronous or service-style code, REST APIs, and working with hardware or network protocols (serial, TCP/IP, OPC UA, or similar).

Software engineering practices. Experience with Git, testing, and code review, and with Docker for deploying software next to hardware.

Protocol translation. Ability to read a protocol, understand what the biology requires, and turn it into a reliable automated workflow.

Communication. Strong communication skills and the ability to train laboratory staff.

Clearance. Ability to obtain and maintain NIH/HHS security clearance and meet federal contractor suitability requirements.

Preferred Qualifications

Direct experience with MADSci, or with similar laboratory orchestration frameworks (for example PyLabRobot, Opentrons tooling, or ROS-based systems).

Experience with simulation platforms such as NVIDIA Isaac Sim, Gazebo, MoveIt, or similar robot simulators.

Experience with stem cell, iPSC, organoid, or tissue engineering laboratories.

Experience with self-driving or autonomous laboratories, including closed-loop experiments driven by ML or optimization.

Familiarity with ROS 2, robot kinematics, and computer vision for labware or sample detection.

Experience with Kubernetes, CI/CD, and message-based architectures (MQTT, Redis, or similar).

Familiarity with LIMS, ELN, and metadata standards, and with FAIR data principles.

Experience with imaging instruments and plate-based assays.

Experience building or using simulation or digital-twin models of robotic systems, or a clear record of learning a new simulator quickly.

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.

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Salary Range

$120,000—$160,000 USD