You will actively participate in our growing team focused on AI-based embedded systems research and contribute to shaping our research agenda. You will develop new methods, models and architectures for embedded AI systems, including domain-specific computer architectures for microcontrollers and FPGAs, with applications ranging from edge devices like microcontrollers to FPGA-accelerated platforms.

• Embedded software and system integration: You will develop embedded software solutions, program microcontrollers and embedded processors, and create complete embedded AI prototypes using development boards, FPGA platforms, and embedded AI modules, including sensor integration, real-time data processing, and communication interfaces for practical applications.
• Hardware-software co-design: You will develop and optimize hardware-software interfaces and participate in co-design development to achieve optimal synergy between specialized hardware and embedded software. This includes machine learning model modification, partitioning, and optimization, with focus on analyzing and implementing the optimal distribution of computational tasks between hardware accelerators and software components to maximize system efficiency and real-time performance.
• Hardware architecture design: You will contribute in the design of digital computing and accelerator architectures, preferably using hardware description languages (VHDL, Verilog, or SystemVerilog) for FPGA implementations and develop domain-specific processor architectures optimized for AI workloads.
• Publication and presentation: You will publish and present results in scientific journals and at conferences to actively contribute to the scientific discussion.
• Leadership and management: You will manage scientific projects and contribute to the strategic direction of our research and expanding the research team. Initiating new third-party funded projects (DFG, BMFTR, EU).
• Teaching and supervision: You will support the preparation and teaching of courses (embedded systems, artificial intelligence/machine learning) and co-supervise doctoral, Master’s and Bachelor’s students
• Interdisciplinary collaboration: You will work in close cooperation with internal and external partners from science and industry to drive technological breakthroughs in applications such as medical technology, smart IoT devices, autonomous systems, and intelligent robotics.