The Position
Internship for 6 Months Project:
Machine Learning / automated analysis of production data and anomaly detection for predictive maintenance applications
Task:
Roche operates a so-called data warehouse in which all production data is collected and analyzed to a certain degree. The data is obtained from hundreds of test fixtures that use various measurement techniques to ensure that the produced instruments and submodules adhere to their specifications.
Currently, the web interface of this data warehouse allows displaying said data, and the backend provides basic functionality that can automatically detect anomalies in the measurement results and trigger alarms. Following an alarm, a production engineer reviews the data and determines whether further action has to be taken or whether the alarm can be ignored.
The tasks for this internship are:
Understand the existing methodology and interface to the data warehouse
Expand the existing algorithms such that predictions can be made when specification limits are going to be exceeded. Include this information in the automated alarms
Evaluate the possibility of distinction between anomalies that require maintenance activities and anomalies that hint towards problems with devices under test
Implement a machine learning algorithm that takes the feedback of production engineers and improves the anomaly detection
Suggest improvements to data collection and analysis, identify gaps in the current implementation
Requirements
Ability to program in one of the languages Python, R, Java, or JavaScript
Technical background familiar with measurement methods and processes
Knowledge of statistical data analysis methods
Fluent in German (due to existing documentation) and English
Preferred:
Pre-existing knowledge in the fields of predictive/preventive maintenance
Studies in engineering or science
Ability to work independently with little supervision
What you can expect
Modern infrastructure of the highest ecological and ergonomic standards
Flexible working environment (in offices as well as home office)
Flat hierarchies where input is appreciated
Opportunity to operate in a vast and diverse network, to realize projects together and get insights in various areas
Working in a fast responsive core team with globally operating stakeholders
Your complete application includes the following documents
A current CV and a motivation letter
A certificate of enrollment (if you are currently studying). If you want to use this opportunity to do a Master’s or Diploma thesis, please highlight this in your application
Due to regulations, non-EU/EFTA candidates must provide a certificate issued by their university stating that an internship is mandatory for the studies and be continuously enrolled at the university
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