Vacancy No. 3614
Research Fellow / PhD Student (f/m/d) Approximate Computing for Deep Neural Networks
In the Department of computer science at the Institute of Computer Engineering, Chair for Embedded Systems (CES), we focus our research on neural network, reliability, and emerging technologies. As a matter of fact, computing systems have reached a point, where significant improvements in computational performance and efficiency have become very hard to achieve. The main reasons are power (density) and efficiency limitations due to the discontinuation of Dennard Scaling as well as increased reliability concerns. Approximate Computing trades off precision against power, energy, storage, bandwidth or performance, and can be applied to hardware, software and algorithms. It promises to re-gain efficient computing by providing additional, adjustable design and runtime parameters to find pareto-optimal solutions. Neural network domain is one of the primary candidates when it comes to approximate computing due to the nature of neural networks which are inherently error tolerant. Accelerating the training and inference of neural network is currently on top of the research focus of both academia and industry.
Expertise in one or more of the following areas is recommended
- Hardware accelerators for neural networks.
- Approximate Computing across the stack, from circuit level through micro-architecture and system-level.
- Modeling the trade-offs in hardware accelerators. Analyzing the resiliency of various neural under different applied approximate computing means.
- Architectural Resiliency of Neural Networks.
The following qualifications are required seeking your consideration for this position.
- MSc degree (or equivalent) in Electrical Engineer or Computer Science.
- Good English skills.
Salary category E13, depending on the fulfillment of professional and personal requirements.
Institute for Computer Engineering (ITEC)
starting July, 1st 2020, or earliest convenience
limited to 3 years and can be extended for two more years
Application up to
Contact person in line-management
For further information, please contact Dr.-Ing. Hussam Amrouch (firstname.lastname@example.org), Tel: +49(0)721/608-45733).
Please apply online using the button below for this vacancy number 3614 .
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phone: +49 721 608-42016,
Kaiserstr. 12, 76131 Karlsruhe
We prefer to balance the number of employees (f/m/d). Therefore we kindly ask female applicants to apply for this job.
If qualified, severely disabled persons will be preferred.