Thesis: Prediction of Learned Surface Embeddings for 6-DOF Pose Estimation

Aufgaben:

You actively support the R&D team in developing an algorithm to predict learned surface embeddings for 6-DOF pose estimation in industrial manufacturing environments In doing so, you familiarize yourself with key concepts in computer vision and point cloud processing, leveraging your current studies in mechanical engineering, robotics, mechatronics, or related fields Building on this foundation, you design and train computer vision models, evaluate their performance on real-world components, and continuously refine your approach based on experimental results Throughout your thesis work, you contribute your own ideas, collaborate closely with experts from various disciplines, and help bridge the gap between simulation and real-world application

Qualifikation:

Education : You are currently enrolled in a degree program in mechanical engineering, robotics, mechatronics, automation, or a comparable field Experience and Skills : You have hands-on experience with computer vision and point cloud processing You possess solid programming skills in Python and/or C++ and have completed independent projects in this area You are familiar with AI-based methods, model architecture design, and evaluating models on real-world data Ways of Working : You demonstrate strong analytical thinking, creativity, and enjoy working independently as well as collaboratively in a team Languages : You have very good English skills, both written and spoken

Wir bieten:

Exciting research and development projects that put your theoretical knowledge into practice Individual supervision and support from experienced experts in your field Access to the latest technologies, laboratories, and resources Diverse opportunities to contribute your ideas and actively shape the projects

Über Uns:

At Siemens, we believe that feeling valued and included is the foundation for doing great work. That's why we aim to create an inclusive workplace where everyone feels a sense of belonging, and where individual perspectives and experiences are celebrated. Our commitment to fairness and respect extends to every applicant. The world never stands still. And new challenges arise every day. With a passion for questioning things, for supplying ideas, and intelligently driving things forward we are helping society move towards a smarter tomorrow. Be it with technologies that reduce carbon emissions in cities or hyperintelligent robots. This is how we are able, to tackle the most important projects and push them forward together. Help us shape the future.