We are seeking passionate and talented students who are eager to shape next-generation products at ZEISS. Integrated within a team of scientists and engineers, you will work on research topics in 3D computer vision and robotics. The project is based on high-precision object tracking involving subtasks such as pose estimation, semantic segmentation and so on leveraging deep-learning methods from computer vision.
Familiarize with the state-of-the-art in pose estimation and tracking applications
Development of the hardware experimental setup based on the use-case
Implementation of prototype solutions relying on methods from both geometric and/ or deep learning methods in computer vision
Validation of the results with test measurements
Evaluation of the technical feasibility
Documentation of the experimental outcomes & test results
As a student, you will work on an equal footing with your colleagues, you will gain deep insights into a company that creates products for the world of tomorrow, and you will create ideal conditions for your later career.
A background in the STEM area (computer science, robotics engineering, electrical engineering)
Currently enrolled in a master’s degree program at a top university
Prior experience with at least one programming language such as C++ or Python
Good theoretical background in linear algebra, optimization, and computer vision methodologies
Experience with CAD modelling software for 3D printing prototype objects will be beneficial
Demonstrable applied experience with the computer vision (such as OpenCV, PCL, Open3D) and deep learning libraries (Tensorflow/ Pytorch) will be beneficial
Self-motivated and independent working style along with a curiosity for diving into challenging topics that push the state-of-the-art
Your ZEISS Recruiting Team:
Franziska Gansloser
