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Using machine-learning to predict motor-performance of Parkinson's disease patients

The project consist in implementing and improving characterization methods of brain signals for decoding of PD-relevant motor-performance.

Deep brain stimulation (DBS) is a standard clinical treatment for advanced stages of Parkinson's Disease (PD). In our lab, we have developed a experimental paradigm that allows to measure motor-performance and brain-signals simultaneously, while undergoing DBS therapy. This is the data you will be working with

Skills required

  • Interest in improving the performance of data-driven neural decoding methods of motor performance relevant to Parkinson's disease.
  • Basic machine learning background.
  • Good programming skills in python (familiarity numpy, sklearn are a plus).
  • Good mathematical background and intuition.
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