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skills in Python, C#, C++, MATLAB, LabVIEW and machine learning frameworks and libraries such as PyTorch, TensorFlow, numpy, OpenCV (mandatory). Embedded systems development (STM32, PIC32, etc). Version
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the analysis of ILs using the following methods NMR, FTIR, DSC, TGA, GC (MS, headspace analysis), viscometry, etc. Have a strong background in the Python programming language, preferably also in machine learning
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. Context: Machine Learning and Artificial Intelligence are topics we frequently hear about, with a wide range of applications, including in the energy sector. However, a key challenge is the lack
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