Postdoctoral Researcher

Purpose

We are seeking a Postdoctoral Research Associate to design and build the automation system for the Autonomous Robotic Metallurgist (ARM), an NSF Materials Innovation Platform at Texas A&M University. ARM is a closed-loop, AI-driven laboratory for alloy discovery that links automated synthesis, thermo-mechanical processing, characterization, and mechanical testing. A campaign layer, driven by Bayesian optimization, decides which experiment to run next. The postdoc will own the system architecture below that layer: the PLC and instrument control, the software that coordinates the stations, and the connection to the campaign logic that plans experiments and consumes their results. The postdoc will work closely with the engineers designing ARM's automated arc melting, rolling, and testing stations, and will be involved in these systems from design through commissioning. We are looking for a robotics, mechatronics, or controls researcher with demonstrated experience in automation, system integration, and PLC programming. Experience with AI/ML-based control is a strong plus. No prior background in metallurgy is required. The appointment is for one year, with renewal contingent on performance and funding.

Responsibilities

• Design the architecture of the automation system, including the control layers, the communication between instruments, and the interface to the campaign logic.
• Work with the equipment designers to define control, sensing, and safety requirements for the arc melting, rolling, and testing stations while they are being built.
• Develop the software layer that turns experimental plans from the Bayesian optimization engine into coordinated instrument actions, tracks their execution, and returns structured results and status.
• Define the interfaces (APIs, message schemas, data formats) through which the campaign logic requests experiments, monitors progress, and handles failed or partial runs.
• Develop and maintain the PLC programs and HMIs that sequence and control the arc melting, hot rolling, and mechanical testing equipment, including I/O, sensor feedback, and data capture.
• Connect the PLC layer to the higher-level Python control software through industrial communication protocols.
• Design and commission robotic sample transfer between processing, characterization, and testing stations.
• Develop and test AI/ML-based methods for control, scheduling, and error recovery, including vision-based monitoring where useful.
• Design safety interlocks, fault detection, and fail-safe routines for unattended operation of high-temperature and high-force equipment.
• Plan staged commissioning, moving each station from operator-approved execution to full closed-loop operation, and test automation sequences in simulation with ARM's digital-twin team before running them on hardware.
• Publish results in peer-reviewed journals and present them at conferences.
• Mentor graduate and undergraduate students and contribute to proposals and sponsor reports.

What we need

Doctoral degree

What is helpful

• Ph.D. in Robotics, Mechatronics, Electrical Engineering, or a closely related field (for example, mechanical, computer, or controls engineering), conferred by the start date
• Demonstrated experience designing and integrating automated systems that combine hardware, sensors, and control software, shown through publications, deployed systems, or code
• Hands-on experience programming PLCs (Allen-Bradley/Rockwell, Siemens, or equivalent) in IEC 61131-3 languages such as ladder logic, structured text, or function block diagram, and developing HMIs
• Experience interfacing software with physical equipment through industrial communication protocols (OPC UA, Modbus, EtherNet/IP, or PROFINET), motion controllers, data acquisition systems, or robot controllers
• Proficiency in Python for instrument control and system integration
• A record of peer-reviewed publications
• Experience with AI/ML-based control, such as reinforcement learning, learned or model-predictive control, or vision-guided manipulation
• Experience building autonomous (self-driving) laboratories or integrating instruments with Bayesian optimization or other decision-making algorithms
• Experience with ROS/ROS2 and with robot arms (UR, FANUC, or similar)
• Experience with safety PLCs and functional safety practice (e.g., IEC 61508 or ISO 13849)
• Experience with digital twins or simulation-based testing of automation sequences
• Experience with computer vision for inspection, sample identification, or quality control
• Experience working with high-temperature or high-force equipment (furnaces, rolling mills, mechanical test frames)

Knowledge, Skills and Abilities

• Strong software engineering skills in Python, including version control, testing, and documentation
• Ability to read and create electrical schematics and wiring diagrams
• Understanding of feedback control, state machines, sequential logic, and fault handling in automated systems
• Ability to specify, wire, and commission PLC hardware, I/O modules, sensors, and actuators
• Ability to design APIs, message interfaces, and data pipelines that connect hardware to optimization and decision-making software
• Strong troubleshooting skills across electrical, mechanical, and software components
• Ability to work independently, set research direction, and communicate results in writing and in talks.