Student assistant "Module Analytics

Student Assistant "Module Analytics"

The Fraunhofer-Gesellschaft is one of the world's leading organizations for application-oriented research. 74 institutes develop pioneering technologies for our economy and society – more precisely: 30 000 people from technology, science, administration and IT. They know:
Anyone who comes to Fraunhofer wants to and can make a difference. For themselves, for us and for the markets of today and tomorrow. As one of the world's largest solar energy research institutes, the Fraunhofer Institute for Solar Energy Systems ISE makes a significant contribution to a sustainable, economical, secure, and socially equitable energy supply worldwide. Our goal is to advance the energy transition by providing concrete, implementable technological solutions through excellent research results, successful industrial collaborations, and spin-offs.

To this end, our ~1,300 employees conduct research in four key areas: energy supply, energy distribution, energy storage, and energy utilization. Fraunhofer ISE's state-of-the-art R&D infrastructure, with 22,300 m² of laboratory space, enables cutting-edge research at an international level. Be part of change Do you want to actively help shape the energy transition and gain practical experience during your studies?

With us, you can do exactly that by contributing to the investigation of the reliability and degradation phenomena of photovoltaic (PV) modules. Our "Degradation Analytics and Modelling" group analyses the degradation of photovoltaic modules and their material components. For our "Degradation Analytics and Modelling" group, we are looking for a student assistant from 1 October 2026. Your tasks include, among others:
You will extract material samples, such as polymers, from PV modules and analyse and evaluate them. You will work with a range of characterisation methods, including colour measurements, FTIR and Raman spectroscopy, microscopy and mechanical load testing and photography. You will document sample preparation and measurement results accurately and transparently. You will independently analyse the measurement results obtained. You will support the preparation and revision of project reports and presentations.

What you contribute

• You are studying natural sciences, engineering or a related field.
• Prior experience in material characterisation is helpful but not mandatory.
• You find it easy to organise your tasks independently and efficiently.
• You are proficient in software for data analysis such as MS Office, Origin or Python.
• You can express yourself confidently in German and/or English, both written and spoken.

What we offer

• Exclusive insight:
  By working together with the scientists in our work unit, you will gain an insight into everyday research and development at a research institute.
• Laboratory infrastructure:
  At Fraunhofer ISE, we work with state-of-the-art facilities and equipment so that research projects can be carried out using the latest technology.
• Research mix:
  We give you the opportunity to combine experimental work with theory and thus apply and expand your knowledge from your studies.
• Supervision:
  You will be supervised in your work by scientists and receive feedback on your progress.
• Teamwork:
  You will gain experience of working in a team by interacting with academic and student staff and will be able to contribute the experience you have already gained.
• Working hours and location:
  We offer you the opportunity to flexibly adapt your working hours to your needs by arrangement and to work from home from time to time.
• Equal opportunities:
  We value equal opportunities and make room for diversity.
• After work:
  Celebrate yourself and your colleagues at after-work events or our annual employee parties.

The remuneration depends on the level of university education attained.

We value and promote the diversity of skills among our employees and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social background, religion, ideology, disability, and sexual orientation and identity. Severely disabled persons will be given preference in case of equal qualification.