Current RIRO-courses

Course
Cycle
Ilias-course
Modern Methods of spectroscopy every semester M-PHYS-106047
Smart Energy System Lab  every semester 2400170
Atmospheric Remote Sensing Infrastructures summersemester 6020247, 4052201
Experimental Design and Analysis: Transport Processes in Rivers summersemester 6222807
Accelerators, synchrotron radiation every semester T-PHYS-104559
Internship autonomous driving every semester T-MACH-113713
Observatory Course every semester M-PHYS-105662
Computational Fluid Dynamics and Simulation Lab every semester 0161700
Boosting the Modern Energy Landscape via Turbo Machines & Machine Learning wintersemester 2169558
The Weather Prediction Chain starts summersemester 2026  
Computational Fluid Dynamics and Simulation Lab, Modelling, Algorithms, Simulation starts wintersemester 2025/26  
AI-based chemical biology starts wintersemester 2025/26  
Advanced DeepLearning in Environmental Sciences    

RIRO GRANTS

Networking research and teaching. Networking of researchers and students.

As a University of Excellence project, 16 competitively selected courses were financially supported in their implementation - our RIRO Grants. Based on the guiding principle of research-oriented teaching, the majority of them follow the concept of research-based learning. This is aimed at ensuring that the responsibility and activities of a teaching-learning setting are primarily in the hands of the students compared to a traditional lecture. Based on the essential phases of a research process, students are actively involved and help to shape the implementation independently (Huber, 2009). 

Depending on the design, both the intensity of supervision and the degree of autonomy in developing a research question can vary greatly. For some RIRO grants, it was the students' responsibility both to identify a question for their research project and to implement it. Other RIRO grants specified the research question to be addressed and/or offered students closer support. However, all RIRO grants are united by the idea of making it possible to experience research at research infrastructures so that teaching becomes an impressive experience.

  • Direct access to large-scale top-level research facilities: Students work at internationally renowned KIT research infrastructures.
  • Excellent supervision: Highly recognized KIT professors are closely involved in the courses and are therefore in direct contact with the students. 
  • Learning through experience: Students are given the opportunity to carry out their own research projects in small groups and under close supervision at state-of-the-art research infrastructures and to apply theoretical knowledge in practical projects.
  • Self-efficacy through personal responsibility: students take the lead and bear significant responsibility for the design and implementation of their research experiments.
  • Sparking enthusiasm for science: carrying out their own work on excellent research infrastructures together with passionate researchers awakens students' enthusiasm for a career in science.
  • Promoting key skills: Skills such as project management, teamwork, creativity and communication skills are strongly encouraged in addition to subject-specific knowledge.
  • Progress through individual feedback and reflection: working in small groups enables lecturers to respond to and support each individual student. Reflecting on the work in the group also contributes to this.