Research Assistant

• Independent research and development in the field of neuromorphic hardware architectures for the intelligent distribution of computational and decision-making tasks between robots and network infrastructures (Edge/Cloud), focusing on energy efficiency, latency, and system stability
• Design, implementation, and evaluation of edge intelligence approaches for networked medical robotic systems - in particular, multi-robot SLAM fusion and privacy-preserving distributed learning
• Development of concepts and algorithms for digital twins to model, predict, and optimize networked robotic operations
• Setup and integration of a testbed as well as proof-of-concept demonstrators for distributed, real-time capable robotic systems to validate energy-efficient data processing and communication methods
• Contribution to scientific publications of project results and participation in the coordination of project activities in close collaboration with the project partner Fraunhofer HHI

• Successfully completed university degree (Master, Diplom or equivalent) in Computer Science, Electrical Engineering, Communications Engineering, or a comparable field
• Strong knowledge in at least one of the following areas:

1. Distributed Robotics: Design and implementation of control approaches for distributed systems and modeling of cooperative robotic systems
2. Al Algorithms and Applications: In-depth understanding of common model architectures and machine learning methods
3. Solid Mathematical Foundations: Linear algebra, functional analysis, and probability theory.

• Programming skills: Proficient in common programming languages and frameworks (e.g. Python, C++, TensorFlow/PyTorch, NumPy)
• Good knowledge of German and/or English required; willingness to acquire the respective missing language skills
• Interest in interdisciplinary research and willingness to collaborate in a dynamic, international team desirable

Please send your application with the reference number and the usual documents combined in a single pdf file, max 5 MB only by email to Slawomir.stanczak@tu-berlin.de.

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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.