In our division »Smart Sensing and Electronics«, we conduct research on embedded sensor solutions that employ machine learning algorithms. Computing on edge devices is gaining prominence with the evolution of Internet of Things.
At Fraunhofer IIS we develop application-specific circuits for edge devices used in industry and research. Further, we develop intelligent algorithms keeping the target hardware in focus. In the direction of development of artificial intelligence on edge devices, we have embarked on a journey of deploying machine learning models on devices that process real-time data with optimal memory footprint.
- You familiarize with the toolchains for deploying neural networks on target hardware
- You implement and test existing algorithms for classifying or analyzing sensor data on embedded devices
What we expect from you
- You are currently studying computer science or a related field
- You have experience in Python and machine learning platforms such as TensorFlow
- You have basic knowledge in the area of embedded systems – microcontrollers and microprocessors
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
- Flexible working hours that allow you to balance your coding and study activities
This position can also be adapted to fulfill requirements of Internships or Master’s theses.
If you have any questions about this opening, please contact Bhargavi Mahesh (firstname.lastname@example.org).
The thesis will be assigned and carried out in accordance with the rules of your university. For this reason, please discuss the topic with a professor who can advise you over the course of the project.
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 53629-SSE. Address your application to Nina Wörlein.
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|Job Reference: 53629||Closing Date:|