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Master’s degree (120 ECTS), with experience in Animal Breeding. Experience with data handling softwares (e.g., R, SAS, Python, Unix Shell) and genetic softwares (e.g., DMU, F90, AIREML). Background in
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; Synopsys or Mentor Graphics. Strong programming skills: Python and C/C++. Experience in hardware accelerators, in-memory processing, or SoC integration. Strong analytical and problem-solving skills, with
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Experience with VLSI design (Cadence tools, Verilog/VHDL, SPICE) Knowledge of neural networks and neuromorphic systems is a strong advantage Good programming skills (e.g., Python, MATLAB) and interest in
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, preferably Reinforcement Learning (e.g., Q-learning, Deep Q-Networks) or other control algorithms. Proficiency in Python, MATLAB, or similar for data analysis, modeling, or AI implementation. Strong written
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and fabrication. The ideal candidates have extensive experience with: Programming of IO boards (STM32, Pixhawk, BeagleBone, etc.) in different programming languages (C++, Python, etc.), MATLAB/Simulink