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Master Thesis / Internship - Evaluate and implement Neural Architecture Search Algorithms (NAS)
The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 30 000 employees work with an annual research budget of 2.9 billion euros.
The »Broadband & Broadcast« department is active in the areas of mobile communications, embedded ML / AI, Internet-of-Things and automotive communication systems. We take new concepts and algorithms in the fields of communications and digital signal processing (e.g. machine learning) from theory, implement them and test them in simulations and in prototypes in our labs and in the field.
You are interested in the field of communication systems and would like to develop further in the field of deep neural networks?
Then have a look at our offer!
Designing neural networks (NNs) involves optimizing many parameters, which make the search space very large. These parameters are for example: The number of layers in NN, the types of each layer, the size of each layer (filters) and the quantization details of each layer. IOften, it is not feasible to optimize these parameters by hand or even by brute force. Therefore, neural architecture search strategies and algorithms, have to be deployed to optimize all the decisions affecting the design of NNs.
In this work, existing solutions of NAS should be identified, implemented and analyzed to one another.
What you will do
-You learn about optimization of deep neural networks
-You identify and compare different existing solutions of NAS
-You research and implement NAS
What you bring to the table
-You are currently studying communications engineering, communications technology, computer science, electrical engineering or a comparable course of study
-You understand deep neural network models
-You know the basics in Python programming
-You have a basic understanding of optimization
What you can expect
-Flexible working hours
-Open and friendly team work
-Varied tasks with room for creativity
-Exciting seminars and events
-Networking with scientists
-Active contribution in applied research
-Interesting an innovative projects
Weekly working hours are determined by agreement. You can start from now on (as an intern for a period of at least three months). You can flexibly determine the working days. After your studies, you have the option of working with us full or part time.
We would be happy to offer you the opportunity to write a master’s thesis in cooperation with us in the above-mentioned subject area. 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.
We value and promote the diversity of our employees’ skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.
With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.
Interested? Apply online now https://jobs.fraunhofer.de/job/Erlangen-Master-Thesis-Internship-Evaluate-and-implement-Neural-Architecture-Search-Algorithms-(NAS)-91058/875239201/ (PDF: cover letter, CV, transcripts). We look forward to getting to know you!
Fraunhofer Institute for Integrated Circuits IIS
Requisition Number: 61690 Application Deadline: none