We offer the following research topic

Thesis - Statistical and ML-based Lifetime Prediction for Automotive HV Batteries 

Master Thesis

TASK:

• Research on the state of the art survival analysis algorithms 
• Examination of possible influencing patterns and failure effects which can be used to predict the remaining battery lifetime
• Implementation of data processing routines and feature engineering algorithms 
• Development of a survival model to predict the remaining lifetime of the individual battery
• Possibility to combine weibull and proportional hazard models (e.g., cox) 
• Investigation and implementation of proper performance metrics to assess the quality of the developed models
• Investigation and implementation of a suitable model validation approach 
• Assessment of the trade-off between the amount of data, model performance and computational time

REQUIREMENTS:

• Attended lectures on the topic of survival analysis
• Proven experience in applying data science methods
• Strong proficiency in Python
• Highly developed quality awareness
• Strong attention to details
• For this thesis your presence at our headquarter in Graz is necessary!

PREFERRED FIELD OF STUDY:

• Applied Statistics 
• Computer Science
• Technological Mathematics
   

The successful completion of the thesis is remunerated with a one-time fee of EUR €3,300.00 before tax.

You don't want to write your final thesis just for the books, then explore the mobility of the future together with us! Maybe you will be a part of it soon!