PhD Position on Deep-Learning Algorithms: This research focuses on designing novel approximate low-power architectures for deep learning algorithms with high dependability, aimed at enabling efficient processing in resource-constrained edge devices.
PhD Position on Investigating Approximate Architectures for Energy-Efficient Processing of Deep-Learning Algorithms
Summary Table:
| HOURS | 40 hr. |
|---|---|
| SALARY INDICATION | Salary gross/monthly based on full-time € 2,770 – € 3,539 |
| DEADLINE | 15 Jun 2024 |
Study Area: With the advent of intelligent Internet-of-Things (IoT), processing Deep-Learning (DL) algorithms in resource-constrained edge devices is challenging.
Scholarship Description: The project investigates approximate computing to design low-power architectures for DL inference in edge devices without compromising accuracy or dependability. Challenges include analyzing effects of approximation, exploring design space, and assessing energy efficiency gains.
Eligibility: You should have an MSc degree in Computer Science, Software/Computer/Electrical engineering, or related fields, with knowledge of computer architecture and digital hardware design. Experience or interest in algorithms, design space exploration, and/or statistical analysis is essential. Proficiency in English is required.
Required Documents:
- A cover letter (maximum 2 pages A4)
- Curriculum Vitae, including courses attended and grades obtained, publications, and references
- IELTS-test, Internet TOEFL test (TOEFL-iBT), or a Cambridge CAE-C (CPE) for non-Dutch applicants
How to Apply: Please send your application via the ‘Apply now’ button below before the 15th of June, including the documents mentioned above.
Last Date: 15 Jun 2024
Interested? Apply now and join our CAES group, fostering an inclusive and collaborative learning atmosphere. For more information, contact Dr. ir. Ghayoor Gillani at s.ghayoor.gillani@utwente.nl.
