Job Information
- Organisation/Company
- Silicon Austria Labs
- Department
- Human Resources
- Research Field
- Engineering » Computer engineeringEngineering » Electronic engineeringTechnology » Computer technologyTechnology » Internet technologyComputer science » Computer architectureComputer science » Computer hardwareComputer science » Computer systemsComputer science » InformaticsComputer science » ProgrammingComputer science » Systems design
- Researcher Profile
- First Stage Researcher (R1)
- Country
- Austria
- Application Deadline
- Type of Contract
- Temporary
- Job Status
- Full-time
- Hours Per Week
- 38.5
- Offer Starting Date
- Is the job funded through the EU Research Framework Programme?
- HE / MSCA COFUND
- Is the Job related to staff position within a Research Infrastructure?
- No
Offer Description
In the "Efficient Algorithms and Accelerator Architectures for Distributed Edge AI Systems", you will explore the world of distributed, decentralized and federated AI systems. These cutting-edge systems enable efficient knowledge sharing between autonomous edge devices, revolutionizing their operational capabilities. This PhD position focuses on exploring space- and energy-efficient edge AI tailored for distributed systems. In contrast to prevailing approaches that focus primarily on inference, this work aims to comprehensively cover the training and fine-tuning aspects of AI.
- Design and implementation of innovative distributed AI methods and algorithms.
- Customizing these methods to unique constraints of power- and resource-limited environments of edge devices and networks.
- Investigate novel accelerator architectures for embedded AI applications, tailoring designs to maximize both performance and energy efficiency.
- Explore the potential for using quantization methods particular attention to the implications for training and fine-tuning neural networks on edge devices.
- Investigate the reliability and resilience of such systems with a particular focus on the influence of the chosen acceleration and quantization scheme.
- Systematically benchmark the designs against existing solutions and evaluate their performance in a variety of use cases. Provide a comparative analysis of energy efficiency, speed and accuracy and demonstrate the competitiveness of the proposed solutions.
- Mentor and guide Masters students, supporting their academic and professional development.
- Contribute to the scientific community by publishing of your research in high-impact journals and presenting your findings at international conferences.
Requirements
- Research Field
- All
- Education Level
- Master Degree or equivalent
- Master's degree in computer science, applied mathematics, robotics, cyber-physical systems, data science, electrical engineering or a related field.
- Strong programming and algorithmic skills.
- Knowledge of hardware description languages is an advantage.
- Experience in machine learning, including deep learning (LSTMs, CNNs, transformers, ...); specific experience in distributed computing systems (fog/cloud computing) and edge systems is beneficial.
- Good communication skills, including basic presentation and scientific writing skills.
- Excellent written and oral communication skills in English.
- Enthusiasm for developing new ideas and a positive attitude towards new challenges.
- Ability to work independently, be well organised, produce high quality documents and meet deadlines.
- Project experience and/or publications in related fields are beneficial.
- Languages
- ENGLISH
- Level
- Excellent
Additional Information
In order for a JS candidate to be eligible for CRYSTALLINE, she or he has to comply with the MSCA-COFUND Doctoral Program (DP) eligibility rules, specific CRYSTALLINE application requirements, and with fundamental ethic principles.
The MSCA-COFUND DP rules require
researchers to (i) be doctoral candidates, i.e., not already in possession of a doctoral degree at the call deadline (whereas researchers who have successfully defended their doctoral thesis but who have not yet formally been awarded the doctoral degree will not be considered eligible), and to (ii) meet the MSCA mobility rule, i.e., have not resided and/or carried out their main activity (work, studies, etc.) in Austria for more than 12 months in the 3 years immediately before the call deadline (time spent as part of a procedure for obtaining refugee status under the Geneva Convention is not taken into account).
The CRYSTALLINE application requirements are met if an applicant (i) holds a master’s degree in a technical discipline, (ii) provides a complete set of application documents, and (iii) complies with the submission rules for the application documents as laid out at the CRYSTALLINE website.
Work Location(s)
- Number of offers available
- 9
- Company/Institute
- Silicon Austria Labs GmbH
- Country
- Austria
- Geofield
Where to apply
- Website
Contact
- State/Province
- Steiermark
- City
- Graz
- Website
- Street
- Sandgasse 34
- Postal Code
- 8010
- human.resources@silicon-austria.com