Fraunhofer Institut für Integrierte Schaltungen IIS
Student Assistant / Intern Multi-view Compression using Deep Learning
- Online seit 09.09.2021
For the Moving Pictures Technology department in Erlangen, the Fraunhofer Institute for Integrated Circuits IIS is currently seeking a
Student Assistant / Intern / Thesis Student
Multi-view Compression using Deep Learning
Capturing and transmitting multiple views or perspectives of a scene allows for a more immersive playback to the spectator. In particular, stereoscopic depth cues can be provided and the spectator is able to change his viewing position when watching the captured scene. This is particularly beneficial for VR applications.
At Fraunhofer IIS, we have developed technologies to compress such multi-view imagery using deep learning algorithms. In order to progress these developments, we are looking for skilled students in the domain of multi-view image processing.
For more information about our light-field research, please refer to https://www.iis.fraunhofer.de/lightfield.
You are interested in the field of Multi-view image processing and would like to develop further in the field of deep learning?
Then we have the right job for you! Your tasks:
- You evaluate existing algorithms and extend them for more flexible use and better achievable quality
- You train the network and evaluate the results using subjective and quality metrics
- You extend the network architecture with new features
What you can expect from us
- An interesting application-oriented field of research with innovative projects and a state-of-the-art laboratory environment
- Extensive professional support from scientific mentors
- Flexible hours that allow you to balance your studies and on-the-job experience
- An open and friendly work environment
- Sufficient opportunity to develop your interests and skills
Weekly working hours are determined by agreement. You can start from now on (as a student assistant: 10-20 hours a week or as an intern: for a period of at least three months).
We can also offer you the opportunity to complete a student thesis in conjunction with our institute in one of the aforementioned fields. The thesis will be assigned and carried out in accordance with the rules of your university. For this reason, please discuss the thesis with a professor who can advise you over the course of the project.
If you have any questions about this opening, please contact: M. Shahzeb Khan Gul (email@example.com).
Please apply for this position using the following link: https://recruiting.fraunhofer.de/Vacancies/62245/Description/2
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 62245-AME. Address your application to Nina Wörlein.
Please let us know how you learned about this job opportunity.
Additional information is available on our website: www.iis.fraunhofer.de/en
- You are currently studying electronics engineering, computer science, information and communication technologies or a related field
- You have experience in programming languages such as Python, MATLAB or C++
- You have a background in using deep learning frameworks such as TensorFlow, PyTorch
- You have good knowledge in the area of multi-view image processing or compression
- Art der Beschäftigung
- Nach Vereinbarung
- Zeitraum der Beschäftigung
- Nach Vereinbarung
- Fraunhofer Institut für Integrierte Schaltungen IIS
- Am Wolfsmantel 33
- 91058 Erlangen, Deutschland
- Frau Nina Wörlein