Augmented Reality Intern: Industrial Parts & Orders Tracking

CSEM SA; Alpnach; Vor Ort; CHF 17.000 - 21.000; Teilzeit

Zusammenfassung

CSEM SA in Alpnach, Switzerland invites motivated students to join a six-month on-site internship to develop an augmented reality system for detecting and identifying parts on an industrial shop floor. The project blends computer vision, object tracking, and 3D visualization to present relevant part information through AR, aiming for a validated PoC tested in real conditions.

Ideal candidates are pursuing a Bachelor's or Master's in CS/EE/Robotics with Python and CV skills, familiar with AR

Qualifikationen

• Pursuing Bachelor’s or Master’s with focus on CV/AR
• Strong Python and CV knowledge
• Experience with AR frameworks beneficial

Aufgaben

• Define system requirements and industrial use cases with the team
• Test AR hardware and libraries
• Set up an experimental environment with industrial parts
• Acquire and annotate image/video data for detection and identification
• Develop and evaluate CV methods for part detection
• Design an AR interface to visualize part information
• Assess robustness under viewpoint, lighting, occlusion, and background changes
• Develop a proof-of-concept demonstrator and validate in realistic experiments
• Document implementation and results and communicate findings to the Predictive Analytics team
• Assist the team with various tasks

Kenntnisse

Python

Computer vision

AR concepts

3D graphics

ML frameworks

Git

Linux

English

German advantageous

Ausbildung

Bachelor's/Master's in CS/EE/Robotics

Tools

AR development frameworks

Camera geometry

Jobbeschreibung

CSEM SA in Alpnach, Switzerland invites motivated students to join a six-month on-site internship to develop an augmented reality system for detecting and identifying parts on an industrial shop floor. The project blends computer vision, object tracking, and 3D visualization to present relevant part information through AR, aiming for a validated PoC tested in real conditions.

Ideal candidates are pursuing a Bachelor's or Master's in CS/EE/Robotics with Python and CV skills, familiar with AR