Apprentice - Experimentation & Systems Engineering

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Skills you'll use

What you'll do

• Design and run controlled experiments on robotic drywall finishing processes using hypothesis-driven and DOE-based approaches
• Identify and isolate independent, dependent, controlled, and confounding variables across physical trials
• Set up instrumentation and measurement workflows; maintain repeatability and reproducibility discipline
• Document observations rigorously and convert trial results into clear experiment logs, test reports, and result summaries
• Analyse cross-system interactions across the robot arm, end-effector, sensors, surface material, and motion parameters to support debugging and process improvement
• Required Qualifications and Skills
• B.E./B.Tech/M.E./M.Tech in Mechanical, Mechatronics, Robotics, Electrical/Electronics, Industrial, Aerospace, or Systems Engineering (candidates from Applied Sciences / Experimental Physics with strong engineering exposure may also be considered)
• 6 months to 2 years of hands-on industry or research experience in an engineering or robotics environment
• Demonstrated experimentation experience in a research lab environment is required
• Understanding of experimental methods, control systems, statistics/DOE, and system design through coursework or projects

Who can apply

• Understanding of experimental methods, control systems, statistics/DOE, and system design through coursework or projects
• Basic knowledge of robotics systems, electromechanical assemblies, sensors, instrumentation, and calibration concepts
• Ability to work with engineering data from physical trials and perform basic statistical analysis and interpretation
• Strong documentation skills — ability to produce structured test reports, experiment logs, and result summaries
• Prior experience with imaging-based experimentation setups (computer vision, machine vision, optical measurement, etc.)
• Hands-on experience with robotics or automation systems — ROS, UR systems, or similar.
• Experience with test setup design, instrumentation, or validation workflows.
• Familiarity with Excel/Google Sheets, Python, or MATLAB for experiment logging, data analysis, and plotting.

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