EEG Signal binary Classification

I have a public dataset of EEG signals that has need basic filtering and noise reduction. I need an expert in machine learning to load the dataset, extract frequency-domain or and time-frequency domain features, and implement a simple classification to determine whether the subject is in an open or closed state, using a method like random forest.

Skills and Experience Required:
- Proficiency in Python for data analysis
- Experience with machine learning, particularly with random forest
- Knowledge of EEG signal processing
- Familiarity with extracting features from time-frequency domain