"Scientist in Cyber-Physical Systems and Digital Twins"

Position Summary:

The UM6P Vanguard Center & UM6P’s School of Applied Sciences & Engineering are recruiting a Scientist in Cyber-Physical Systems and Digital Twins to lead technology-driven projects within the Wicked Problems (WiP) learning framework. This role bridges physical systems and their digital counterparts, focusing on the design, simulation, and real-time control of interconnected smart systems in domains such as manufacturing, energy, mobility, health, and agriculture.

Key Responsibilities:

• Mentor student teams in the design and implementation of cyber-physical systems (CPS) integrating sensors, actuators, control algorithms, and embedded systems.
• Guide the development and deployment of digital twins for real-world processes and infrastructures (e.g., factories, greenhouses, robotics platforms).
• Support modeling, simulation, and data-driven optimization using tools such as ROS, Unity, Modelica, Simulink, and SCADA platforms.
• Collaborate with faculty and industrial partners to create prototyping kits, demonstrators, and hybrid (hardware-in-the-loop) systems for education and applied research.
• Ensure integration with operational technologies (OT) such as edge computing, PLCs, industrial protocols (OPC-UA, Modbus), and digital platforms.
• Co-author technical reports and academic publications emerging from student-led and co-supervised projects.
• Publish research and co-author student-led publications resulting from WiP investigations.
• Contribute to applied research motivated by the WiP investigations.

Required Qualifications:

• Ph.D. in Mechatronics, Robotics, Systems Engineering, Computer Engineering, or a related field.
• Proven experience with cyber-physical systems design, real-time control, and digital twin development.
• Proficiency in C/C++, Python, MATLAB/Simulink, and relevant CPS software frameworks (e.g., ROS, Unity, SCADA).
• Understanding of embedded systems, communication protocols, and systems integration.
• Strong interest in student mentorship and interdisciplinary, applied learning environments.

Desirable Qualifications (at least two of the following):

• Experience with edge/cloud computing platforms for industrial or IoT-based systems.
• Familiarity with simulation-to-hardware pipelines, predictive maintenance, or hybrid modeling.
• Background in smart agriculture, mobile robotics, or automated manufacturing systems.
• Engagement with open-source ecosystems and development of reusable CPS modules or demonstrators.
• Interest in educational robotics and digital twin-based curriculum development.

Cross-Domain Application Areas May Include:

• Industrial automation and predictive maintenance
• Smart farming and greenhouse management
• Autonomous vehicles and mobile robotics
• Healthcare systems and assistive technologies
• Urban infrastructure and environmental monitoring