Fraunhofer-Gesellschaft

Internship: Data Management in Python

Fraunhofer-Gesellschaft · Dresden, Saxony, Germany

Research Services · 51-200 employees

13 h ago
Junior (0-2 yrs) Internship Germany
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About the role

You will be responsible for improving and implementing automated procedures for processing and visualizing large amounts of physical measurement data. Additionally, you will maintain the existing codebase and develop new features for data automation.

What they look for

Python Data Management Data Visualization Data Processing Automation Code Maintenance Applied Physics Software Development Technical Documentation Silicon Wafers Electronic Components

Requirements

The role requires proficiency in Python for data manipulation and the ability to translate physical knowledge into functional programming code. Candidates should be capable of producing clear documentation and working within interdisciplinary teams.

Full description

Developing innovative technology solutions and bringing them to application - that is our goal at the Fraunhofer Institute for Photonic Microsystems IPMS. With our expertise in the development of photonic microsystems, related technologies including nanoelectronics and wireless communication solutions, we create - in flexible and interdisciplinary teams - technologies for innovative products in a wide range of markets such as automotive, industrial and aerospace.

At Fraunhofer IPMS, in the business unit »Emerging Memory Solutions«, new electronic components are being developed. During the characterization of these components on 300 mm silicon wafers, extensive physical measurements generate large amounts of data. Efficient preparation of this data is therefore crucial for short learning cycles. Your role focuses on improving and implementing procedures for the automated processing and visualization of this data using Python.

Be part of change

  • Raw data manipulation: Handling and transforming raw data within software applications
  • Code maintenance: Maintaining and continuously improving the existing codebase
  • Feature development: Implementing new features for data visualization, processing and automation
  • Applied physics: Translating physical knowledge into functional programming code
  • Documentation: Producing clear and comprehensive code documentation