Wissenschaftliche*r Mitarbeiter*in (m/w/d) im Bereich "Transfer Learning für KI-Anwendungen auf Basis von Low-Cost FPGAs“ // Research Associate in the area of “Transfer learning for AI applications based on low-cost FPGAs“

Unser Angebot:

• Eine offene Gespräche- und Führungskultur, in der Disskussionen auf Augenhöhe geführt werden und neue Ideen willkommen sind, kennzeichnen unsere Zusammenarbeit
• Sie arbeiten in einem internationalen Team
• Individuelle Förderung
  

Bei inhaltlichen Fragen zur ausgeschriebenen Stelle wenden Sie sich bitte an Herrn Prof. Thilo Pionteck unter: Tel. 0391/67-57148 bzw. per E-Mail: thilo.pionteck(at)ovgu.de.

Sie profitieren von unseren Strukturen und Angeboten für Nachhaltigkeit, Diversität, Familienfreundlichkeit und Personalentwicklung. Unser Standort im Zentrum einer florierenden, belebten und familienfreundlichen Landeshauptstadt garantiert eine hohe Lebensqualität und vielfältige Freizeitmöglichkeiten. Weitere Informationen erhalten Sie unter www.ovgu.de/karriere und unter www.eit.ovgu.de.

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Ihre vollständige Bewerbung (Motivationsschreiben, Lebenslauf, Zeugnisse) senden Sie bitte bis zum
31. Januar 2025 über das Online-Bewerbungsportal.

We are a university with a focus on engineering and natural sciences as well as economics, human sciences and medicine. We offer excellent study and working conditions to 13,000 students from Germany and abroad as well as approx. 3,000 employees.

The Chair of Hardware-oriented Technical Computer Science (HTI) focuses on the design of runtime-adaptive, performance- and energy-efficient heterogeneous system architectures. A holistic approach is pursued, which enables optimal adaptation of the hardware and software architecture as well as system management to the requirements of the application and the technological possibilities of the hardware platforms used.

Job description:

You will be working as part of a research project on the energy- and resource-efficient realization of transfer learning approaches on edge devices. The aim is to develop approaches and hardware architectures that allow transfer learning for AI applications to be implemented on FPGAs with limited resources. This should enable edge devices to react autonomously to changing requirements or environmental characteristics without transferring data to the cloud. To this end, it is necessary to investigate how existing approaches for transfer learning can be implemented in a hardware-efficient manner and, if necessary, further developed. The results will then be made available as flexible and easy-to-use open source IP cores.

The opportunity for scientific qualification as part of a doctorate is given and is supported accordingly.

Requirements profile:

• completed scientific university education (diploma/master's degree) in the fields of electrical engineering, computer science or a related subject with an overall grade of at least “good”
• very good knowledge of a programming language, e.g. C, C++
• Knowledge of digital circuit design for FPGAs and/or artificial intelligence
  
• high degree of independence, good communication and teamwork skills, desire to do a doctorate
• Support of the chair in the implementation of German-language exercises and seminars
• good language skills in German and English

Your benefits:

• Our collaboration is characterized by an open culture of communication and leadership, in which discussions are held at eye level and new ideas are welcome
• You work in an international team
• Individual support
  

For further information about the position, please contact Prof. Thilo Pionteck at: Tel. 0391/67-57148 :/Mail thilo.pionteck(at)ovgu.de:

You will benefit from our structures and offerings in the fields of sustainability, diversity, family support and staff development. Our location in the center of a thriving, lively and family-friendly state capital guarantees a high quality of life and a wide range of leisure activities. For more information, please visit www.ovgu.de/en/karriere or www.eit.ovgu.de/en/.

Otto von Guericke University Magdeburg is a signatory of the German Diversity Charter. We welcome your application, regardless of gender, cultural and social background, age or sexual orientation. Applications from severely disabled people or people with an equivalent impairment will be given priority in the case of equal suitability, ability and professional expertise. Otto von Guericke University Magdeburg strongly promotes gender equality in all professional areas.

Please note the information for storage of personal data: https://www.ovgu.de/en /data_protection.html.

Please send your complete application (motivation letter, curriculum vitae, graduation certificates, references) by January 31, 2025 using the online application portal.