The Fraunhofer Institute for Solar Energy Systems ISE in Freiburg is Europe's largest solar research institute. Our approximately 1,400 employees work towards a sustainable, economical, secure, and socially equitable energy supply system based on renewable energies. We contribute to this through our research focuses on energy provision, energy distribution, energy storage, and energy utilization. With outstanding research results, successful industry projects, company spin-offs, and global collaborations, we shape the sustainable transformation of the energy system.
Would you like to actively contribute to the energy transition and gain practical experience during your studies? With us, you work towards realizing this goal. In our group "Concentrating Systems and Technologies," we research the next generation of CSP hybridization. Concentrating solar technology (CSP) is an environmentally and climate-friendly method of power generation, particularly relevant in regions with strong direct sunlight. A key strategy to increase the cost efficiency and reliability of CSP power plants is hybridization, where renewable energy sources or storage technologies are combined with concentrating solar technology. Through software simulations and modeling, we can optimize the quality, efficiency, functionality, and control of hybrid systems.
For our group "Concentrating Systems and Technologies," we are looking for a student assistant as soon as possible.
What you will do
* You support the further development of our in-house software ColSimCSP, which specializes in the design and simulation of hybrid concentrating solar systems.
* You expand various software models for hybrid power plants and enhance their components.
* Your tasks also include evaluating simulation results and validating your implementations.
* You conduct techno-economic optimization studies for future publications.
* You work with object-oriented and modular programming (C++/Python) and document your code.
What you bring to the table
* You study computer science, physics, engineering or a comparable field.
* You have programming experience (Python) and have already worked on multi-objective optimization projects.
* You are interested in the overlapping research of machine learning, neural networks and renewable energy technologies.
* You have a very strong command of English.
* You are looking for a field of work as a student assistant in which you can creatively apply and expand the knowledge you gained during your studies.
* You are potentially interested in a follow-up bachelor or master thesis.
* You are comfortable working in a dynamic environment and enjoy taking on new challenges.
* You can work in a team as well as independently on given tasks.
* You like to work creatively and bring your own ideas and suggestions for improvement into the team and into the project.
* We are looking forward to your meaningful application including CV, transcript of records from university and earlier references
What you can expect
* Exclusive Insight: By working alongside the scientists in our unit, you gain insight into the daily life of research and development at a research institute.
* Research Mix: We offer you the opportunity to combine experimental work with theory, allowing you to apply and expand your knowledge from your studies.
* Mentorship: You will be guided by scientists during your work and receive feedback on your progress.
* Teamwork: Through interaction with scientific and student staff, you gain experience in teamwork and can contribute your existing experiences.
* Working Hours and Location: We offer you the flexibility to adjust your working hours to your needs and occasionally work from home.
* Equal Opportunity: We value equal opportunities and provide space for diversity.
* After Work: Celebrate yourself and your colleagues at after-work events or our annual staff parties.
The compensation is based on the level of higher education completed. The monthly work time should be 30-80 hours.
We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.
Interested? Apply online now. We look forward to getting to know you!
Fragen zu dieser Position beantwortet Dir gerne:
Nicholas Chandler
Tel.: +49 761 4588 5969
Fraunhofer Institute for Solar Energy Systems ISE
www.ise.fraunhofer.de
Requisition Number: 79366 Application Deadline: