Within our team, you will work on the validation of an algorithm that detects certain driving events in vehicle big data (i.e. driving over a speedbump) and estimates the forces experienced by the vehicle during these events. As the forces are not measured on the vehicle, they are derived from indirectly correlated sensors through machine learning. Your activities consist of:    

• Applying the algorithm to existing big data set and determining the location of the events.
• Setting up a validation experiment at the location derived from big data together with our testing team.
• Analysing and comparing the measurement data to the output of the algorithm.
• Based on the gathered data, expanding the algorithm to detect other events and classifying them according to their severity.

• You are fluent in English (TME’s business language)
• You have a background in data analysis and science including machine learning techniques, experience in Python (Scikit-learn, statsmodels, keras,…) is an asset
• You have some knowledge of mechanical engineering, testing
• You have strong analytical problem solving skills reinforced by good common sense
• You are a quick and eager learner with a flexible mind and good eye for details
• You are a team player with good communication skills inside a multicultural environment
• You are self-organized and can manage your time.

It is mandatory that applicants are students for the entire period of the internship.