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FEMTech internship – Data analytics (28,5h/week)

Thematically, we are looking for a Master's student with a technical background or a student who would like to focus more on modeling, machine learning, and complexity science. The thematic focus of the internship is on the application or further development of methods for data collection, pattern recognition, feature extraction, and data transformation in a machine learning context. As we are in close contact with national and international corporations, SMEs, start-ups, universities and technical colleges, our team has a wide-ranging technical know-how. SBA Research therefore offers an interesting environment to gain first research and professional experience.

This internship is based on the requirements and framework conditions of the FFG's FEMtech program and is aimed at women who would like to gain professional experience in the technical field.


Your tasks:

  • Collaborate on exciting research projects to model interactions and interdependencies of complex systems (e.g., critical infrastructures, software, environment).
  • Acquisition and analysis of quantitative data (open access data, Python, R, etc.)
  • Application and further development of machine learning in collaboration with technical experts
  • Interdisciplinary topics and communication of research results

Profile:

  • Bachelor's degree in e.g. (business) computer science, physics, electrical engineering, geography
  • Basic knowledge in statistical analysis and visualization
  • Basic knowledge in Machine Learning (optional)
  • Interest in interdisciplinary topics
  • Basic knowledge in Python
  • Problem solving skills and curiosity for new topics

Your benefits:

  • Attractive working environment in a motivated team
  • Creative freedom in the execution of tasks
  • Flexible working hours and possibility to work from home
  • Free fruit, coffee, mate, etc.
  • Supervision by experienced researchers

Salary: € 1.400,00 gross/month

Start of the internship: Earliest start March 2024 (individually agreed)

Apply now

Bei Fragen kontaktieren Sie uns unter kmallinger@sba-research.org