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Field
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science and machine learning Knowledge with Python or Matlab. Application process Please send your CV, academic transcripts and brief rationale why you want to join this research project via the HDR
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/robotic systems Ability to implement control and kinematics with hardware-in-the–loop Background with relevant packages, (MATLAB, SolidWorks/Creo, ROS/ OpenCV/ python, LabVIEW/C languages) A driven
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packages, (CREO/SOLIDWORKS, ANSYS/ABAQUS, MATLAB) •A driven, professional and self-dependent work attitude •Experience of working within industry will be an advantage •The ability to produce high-quality
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to implement control and kinematics with hardware-in-the–loop ◾Background with relevant packages, (MATLAB, ROS/ OpenCV/ python, LabVIEW/C languages) ◾A driven, professional and self-dependent work attitude is
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-varying signals (e.g., acoustic signals, movement tracking). Coding experience (e.g, MATLAB or Python). Intrinsic motivation to conduct research in the topic of the project. Committed to working
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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
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) applications in the power grid. • Experience with power system modeling, simulation, dynamics and/or optimization, phasor and electromagnetic transient (EMT)-based modeling, and Python and/or Matlab
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soil characterization techniques. A strong command of English is indispensable. Skills in R, MATLAB or Python are helpful. The effective exchange within the interdisciplinary collaboration will be