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with industrial communication protocols (e.g., CAN, Modbus); and experience with embedded C/C++ programming for implementing control algorithms on DSPs and FPGAs. Ability to lead a team and work
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develop innovative laser medical technology processes and systems in an interdisciplinary team. Your tasks will range from the design and implementation of FPGA-based real-time control systems
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) Rapid Prototyping (3D printing, Raspberry Pi, FPGA) Electrode patterning and cleanroom fabrication techniques Good team player with strong interpersonal skills Entry level applicants will also be
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Qualifications (optional but advantageous) 1. Experience with FPGA programming (Verilog/VHDL) for real-time data acquisition or signal processing; 2. Familiarity with PCB design and layout (PADS, Altium, KiCad
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physics (HEP) detectors, neuromorphic computing, FPGA/ASIC design, and machine learning for edge processing. The successful candidate will work with a multi-institutional and multi-disciplinary team
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, depending on your skills, integrating hardware accelerators (FPGA) into "Hardware-in-the-Loop" simulations. Finally, you will actively participate in the scientific dissemination of the work through the
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for accelerators, such as GPUs or FPGAs. Experience in refactoring or porting large codebases (over 100k source lines of code). Background in supporting scientific code on HPC systems or familiarity with components
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Design). Ideal candidates have Specialist Knowledge in Neuromorphic Engineering, with experience in Designing and Building and Implementing FPGA systems, working with and/or developing neuromorphic
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platforms, including embedded and edge computing environments (e.g., Jetson, Raspberry Pi, FPGA, neuromorphic chips) Publish results in top-tier journals and present at leading international conferences and
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, ONNX, TensorRT, FPGA) is an advantage Ability to work across disciplines - mechanics, ML, hardware, medicine We offer Multilingual and international character. Modern institution with a personal