For the »Moving Picture Technologies« department in Erlangen, the Fraunhofer Institute for Integrated Circuits IIS is currently seeking
Student Assistants Machine Learning for Image and Video Compression

The »Moving Picture Technologies« department is part of the »Audio and Media Technologies« division of Fraunhofer IIS, which constitutes one of the world’s largest organizations dedicated to audio, speech and media processing. It has been an innovator in sound and vision for over 25 years and repeatedly won international competitions in the audio and media field: e.g. with mp3 and codecs of the AAC-family. Over 200 engineers and scientists develop first-rate technology, which is sold worldwide, in Europe, USA, China, Korea and Japan.

The future of image and video compression will be affected by latest machine learning developments such as Variational AutoEncoders (VAE) and Generative Adversarial Networks (GAN). We are looking for passionate students willing to work on this topic by studying, evaluating and implementing novel concepts in machine learning for image and video compression.

What we expect from you

  • You are studying electrical engineering, computer science, information and communication technologies or a related field
  • You have experience in programming languages such as C++, Python or MATLAB
  • You know how to build a custom neural network from scratch
  • You have experience with deep learning frameworks such as TensorFlow, PyTorch, Caffe or Theano
  • You are familiar and have hands-on experience with VAEs and GANs
  • You have basic knowledge in the area of image and video processing

What you can expect from us

  • An open and cooperative working environment
  • Collaboration in interesting and innovative projects
  • Many opportunities to gain practical experience and attend seminars
  • Flexibility concerning your working hours

The weekly working time is determined by agreement, but you should be available for at least 12 hours per week.

Applications are possible in German and English. Please include a cover letter, your CV and your latest transcripts of records (as PDF) and quote ID number 53361-AME. Address your application to Nina Wörlein.

Please let us know how you learned about this job opportunity.

Job Reference: 53361-AME Closing Date: