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of this highly promising modern technology. Deep learning methods are highly effective when targeted and precisely utilized. Incorporating explainable mechanisms will thus strengthen the expertise of biomedical
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aspects of the machine learning pipeline, such as feature engineering, model selection, and hyperparameter tuning. This enables individuals with limited machine learning expertise to build and deploy
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. The simulated robot data is easier to construct, but still requires much engineering work to create scripts and suffers from a sim-to-real gap. The real-world Internet data though is large-scale and contains real
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equivalent) in Computer Science, Computer Engineering, or Electrical Engineering. Languages: proficiency in written English and fluency in spoken English required. Relational skills: the candidate will work in
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the intersection between biomedical engineering, complex systems and clinical neuroscience. NERV proposes new computational frameworks to analyze and model the spatiotemporal complexity of brain networks from