ZEISS
Internship/MasterThesisondevelopingtrackingmethodsfordeformableobjects(f/m/x)
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optimal for Entry candidates.
“Internship/ Master Thesis on developing tracking methods for deformable objects (f/m/x) at ZEISS. Skills: computer vision, robotics, deep learning. Familiarize with state-of-the-art. Development of hardware setup”
What They're Looking For.
Must Have
programming in Python, linear algebra, optimization, computer vision methodologies
Nice to Have
applied experience with computer vision, deep learning libraries, PyTorch
What You'll Do.
Familiarize with state-of-the-art
Development of hardware setup
Implementation of prototype solutions
Validation of results
Evaluation of technical feasibility
Documentation of outcomes
How You'll Work.
Team & Collaboration
Integrated within a team of scientists and engineers
Full Job Description
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 developing computer vision methods for robust tracking of deformable objects. # **Your Role** With us, you have the opportunity to perfectly combine your studies with practical experience while actively contributing to exciting projects. This allows you to gain valuable skills, expand your network, and grow both professionally and personally. * 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 and robotics * Validation of the results with test measurements * Evaluation of the technical feasibility * Documentation of the experimental outcomes & test results # **Your Profile** * A background in either computer science, robotics engineering, or electrical engineering and currently enrolled in a master’s degree program * Strong experience with programming in Python * Good theoretical background in linear algebra, optimization, and computer vision methodologies * Demonstrable applied experience with computer vision and deep learning libraries (e.g. 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 Sounds exciting? Then become part of #teamZEISS and help us shape the future! Please provide your complete application documents (CV, transcript of records, etc.). Your ZEISS Recruiting Team: Franziska Gansloser
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