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packages and tools (e.g., Numpy, Pytorch, Tensorflow, ART). You have knowledge or familiarity with reverse engineering tools (e.g. NSA Ghidra, IDA Pro) You have experience with Python, C/C++, or low-level
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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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/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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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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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big
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of space and plasma physics Data analysis Programming skills (e.g., Python, Matlab, and/or C/C++) Proficiency in both written and spoken English. Terms of employment The employment is expected to result in a
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. PV field system data analysis (time-series data analysis with JMP software and /or Python). Accelerated ageing procedures (IEC standards). PV module failure modes. Corrosion. Strong communications
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be considered if combined with advanced coursework in cell and molecular biology and genetics. Experience working in a Unix/Linux environment, as well as documented experience in R or Python, is
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criteria for the position. Preferred selection criteria Familiar with SPSS, STATA, R, or Python for quantitative analysis Knowledge of NVivo or Atlas.ti for qualitative data analysis Personal characteristics
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requirements for admission to the faculty's Doctoral Programme You must have good written and oral English language skills Experience with programming in Python or similar languages