Facts
- Number of employees
- ca. 7000
- Category
- Research assistant
- Job location
- Germany, Berlin, Charlottenburg
- Area of responsibility
- Academia and research, Research (academic), Teaching (university)
- Start date (earliest)
- 01.10.2026
- Duration
- for 5 years
- Full/Part-time
- full-time; part-time employment may be possible
- Remuneration
- Salary grade 13 TV-L Berliner Hochschulen
- Homepage
- http://www.tu-berlin.de
Requirements
- Qualification
- Master, Diplom or equivalent
Contact
- Reference number
- IV-373/26
- Contact person
- Prof. Dr. Kao
Apply
- Application deadline
- 02.10.2026
- Reference number
- IV-373/26
- By email
- odej.kao@tu-berlin.de
Research Assistant - 1st qualification period (PhD candidate)
part-time employment may be possible
Your responsibility
Research and teaching tasks in the research group Distributed Operating Systems (DOS).
Development and experimental evaluation of methods for reliability of Al infrastructures, distributed Al training and inference, energy efficiency and performance optimization for Al infrastructures. Further development of our observability tools for computing infrastructures and energy systems to analyze and evaluate the behavior and sustainability impacts of large-scale Al deployments. Publication of research results in international conferences.
Your profile
- Successfully completed university degree (Master, Diplom or equivalent) in Computer Science or a closely related field
- Solid research experience in Al infrastructure management, energy-aware computing, or the resource-efficient operation of large-scale computing infrastructures
- Strong background in machine learning and artificial intelligence, with particular emphasis on Al systems for training and inference at scale
- Experience with performance, efficiency, and resource modeling of modern Al workloads, including accelerator-based computing and large-scale model deployment
- Expertise in data-driven modeling, forecasting, and optimization methods for evaluating and controlling system behavior
- Excellent programming skills in Python and experience with scientific computing, machine learning frameworks (e.g., PyTorch), and optimization tools
- The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills.
- Experience with scalable data analysis, distributed systems, and cloud or data center infrastructures. - Familiarity with reliability and fault tolerance for Al inference and training is highly desirable
- Strong experience in publishing and presenting scientific results as well as in teaching and mentoring students desirable
- Ability to conduct independent scientific work and to collaborate successfully with interdisciplinary and industry partners desirable
How to apply
Please send your written application with the reference number and the usual documents
(CV, list of grades, language certificates) to Technische Universität Berlin - Die Präsidentin - Fakultät IV, Institut für Telekommunikationssysteme, FG Distributed and Operating Systems (DOS), Herrn Prof. Kao, online only: odej.kao@tu-berlin.de.
By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/.
To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.