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Project title: Developing and Evaluating Interpretable Approaches for Human-Centered Machine Learning.Project description: Approaches in interpretable machine learning offer promise in understanding
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tools such as LTSpice (preferred)/TINA/Multisim. Knowledge of low-power biopotential amplifier design and energy harvesting techniques is preferred. Candidates with machine learning skills, particularly
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or equivalent) Experience with machine learning tools (e.g., Scikit-learn, Tensorflow, PyTorch, etc.) Track record of publications/and conference papers in software modelling or programming, or system level
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hyperspectral data acquired from outcrops, drill cores and UAVs into a single 3-D model that, with the aid of machine learning protocols, can be upscaled to facilitate regional mineral exploration strategies in