Fully Funded PhD and Teaching Assistant Position in Robotics at MTU

Michigan Technological University

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Description

Michigan Technological University (MTU) is currently accepting applications for a fully funded PhD opportunity that includes a Teaching Assistant position. This academic role is based in the Robotics and Remote Sensing Lab (RRSL), which operates within the Applied Computing Department and the Department of Manufacturing and Mechanical Engineering Technology. The selected PhD student will begin their research and teaching duties in the Fall 2026 term. The core research for this program centers on leveraging industrial digital twins applications. Students will focus on modeling the behavior of physical systems and designing simulated what-if scenarios to test these models.  

Target Audience

• Prospective PhD students who already hold a Master's degree in a relevant technical discipline.
• Special preference is given to candidates currently studying at MTU and those with prior experience working with digital twins.

Funding Coverage Breakdown

• This program is explicitly listed as a fully funded PhD opportunity.
• The financial support is provided through a Teaching Assistant position within the university. 

Eligibility & Preferred Qualifications

To be considered for this competitive research and teaching role, applicants should meet the following technical and academic preferences:

• Hold a Master's degree in Mechatronics, Mechanical Engineering, Robotics, Computer Science, Electrical Engineering, or a closely related academic field.
• Have successfully published at least one academic paper.
• Possess strong programming skills in Python, specifically demonstrating familiarity with automation, system integration, or data processing.
• Have practical, hands-on experience using ROS 2.
• Demonstrate previous experience in CAD or 3D modeling.
• Show experience with physics-based modeling, which may include motion dynamics, material flow, conveyor systems, or process and sensor modeling.
• Have experience with real-time data acquisition, edge devices, sensors, IoT systems, or microcontrollers such as Raspberry Pi and Arduino.
• Be familiar with virtual modeling or simulation software environments, such as Unity or NVIDIA Isaac.
• Prior teaching experience is highly preferred, particularly if it is in the subjects of Machine Learning and Digital twins. 

Application Process

• Interested candidates must submit their application by completing the designated online form.
• The official application form can be accessed directly at: https://lnkd.in/defrgV6j.
• If students have specific inquiries or require further information about the lab or the position, they can contact the organizers via email at amazen@mtu.edu.

Important Deadlines

• Applications are actively being reviewed on a rolling basis.
• The application window will remain open and evaluations will continue until the Teaching Assistant position is officially filled.