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Internship/ Master Thesis on developing tracking methods for deformable objects (f/m/x)

ZEISS Group
Found 2 months ago
Location
Oberkochen, Germany
Duration (Months)
3 Months
Time
Full-time
Work Mode
On-site
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Master

Skills & Qualifications

Technical Skills

  • Computer Vision
  • Robotics
  • Python
  • linear algebra
  • optimization
  • PyTorch
  • deep learning libraries

Soft Skills

  • Self-motivated
  • independent working style
  • curiosity

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

Requirements

  • A background in either computer science, robotics engineering, or electrical engineering and c urrently 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

Related Field

  • AI & Machine Learning

Related Subfield

  • Computer Vision

Languages

  • English

Nice to Haves

  • Demonstrable applied experience with computer vision and deep learning libraries (e.g. PyTorch)
▶Apply Now

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