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-level layer implementations - extend hardware developments to use near-FPGA DDR and HBM memories - create functional demos using networks of interest (Yolo, Resnets, LLMs, ...) - create proof-of-concept
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of Applied Engineering is looking for a full-time (100%) doctoral scholarship holder in the field Biomimetic Echolocation and Autonomous Aerial Robotics with a focus on FPGA-based sensor design and signal
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-hardware co-design of neural architectures, memory hierarchies, and communication systems Model compression and optimization (pruning, quantization, knowledge distillation) for edge deployment FPGA- and ASIC
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degree in computer science, mechatronics, or electrical engineering. Strong programming skills (C/C++, Python; hardware description languages such as HLS or VHDL are an advantage). Knowledge of computer
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, Digital signal Processing (punctuation: 25) Item 03: Experience in: RF design for satellite comm, FPGA programming in VHDL., PCB design for RF (punctuation: 25) Item 04: Personal interview. The interview
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criteria Candidates must have relevant professional or academic experience in Radio Access Networks, physical layer of communication systems, software defined radios, microcontroller-based systems, FPGA/SoC
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position focused on the development of low-power SiPM-based radiation detectors for space missions. The selected candidate will be involved in the data analysis for the quality control of ASICs developed
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into the co-design of ultra-low-power AI hardware architectures tailored for edge computing applications. The research aims to develop neuromorphic processors, FPGA/ASIC-based AI accelerators, and intelligent
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is desirable. Basic understanding of embedded systems and processor architectures. Strong programming skills (C/C++, Python; hardware description languages such as HLS or VHDL are an advantage
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description languages such as HLS or VHDL are an advantage). Motivation to pursue a PhD and contribute to applied AI research. Excellent English skills. Where to apply Website https://jobs.uni-siegen.de/job