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Internship –Wave Optical Simulations for Micro-optical Structures (f/m/x)

  • Oberkochen
  • Internship
  • Posted
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Skills

  • Communication
  • German
  • Problem Solving
  • Python
  • Recruiting

Job description

For a variety of modern optical systems, reliable characterization and simulation of wave-optical propagation effects is crucial. Depending on the application, this may involve selecting, adapting, or comparing different numerical approaches, ranging from efficient wave-propagation algorithms to rigorous solvers such as finite-difference time-domain (FDTD) methods and related techniques. The choice of a suitable method with respect to numerical complexity, performance, and accuracy therefore plays a fundamental role. As part of this internship or thesis, promising approaches will be investigated and compared for relevant application examples, such as optical waveguides, photonic integrated circuits, printed micro-optic components, or semiconductor optics. This project within ZEISS Corporate Research and Technology provides insight into a highly dynamic R&D environment with many exciting research fields.

Your Role

•Screen literature and open-source codebases
•Select suitable wave-optical propagation algorithms and approaches from in-house or open-source implementations
•Select relevant use cases and appropriate evaluation metrics
•Develop Python code for the evaluation and visualization of various tools and algorithms for selected applications
•Conduct simulations and analyze results
•Document and present results

Your Profile

•You are enrolled in a Bachelor’s or Master's program of physics, optics, or mathematics
•You have basic knowledge of optics
•You have basic programming skills in python
•You have excellent organization, problem-solving, communication, and innovation skills
•You are fluent in English and German

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