The trip in April will be postponed!

Each year, the Foreign Lustrum Excursion Foundation, or SLEF, organizes an excursion to a foreign (European) country for members of T.F.V. 'Professor Francken', visiting universities and companies to get an impression of the world of engineering physics outside of Groningen. Furthermore, with a lustrum, the committee goes all-out and organizes an excursion to another continent, broadening the horizon even more.

In 2021 we'll organize a new excursion to Italy and Switzerland. The original plan was to leave in April, but the trip will be postponed due to the coronavirus.


For students

To finance the foreign excursions and keep the participants' fee as low as possible, the foreign excursion committee provides so-called case studies. A case study is an assignment by a company under supervision of a PhD or professor at the RUG. It could be anything from purely theoretical research to a practical assignment. The student doing such a case study is rewarded ECTs, which can be used for the mandatory bachelor project or master project. Our job is to arrange these case studies, and initiate contact between students, the university and companies.

Thereby, the student doing a case study receives a so-called wild card for the foreign excursion. This means that he or she will have guarantee to join the lustrum excursion in 2021 to Italy and Switserland. If you are interested in doing a case study or want to know more, send us an email.

Case studies (for companies)

A company can hire students who follow their education at the University of Groningen (RUG) to do a so called case study, which is an assignment by a company under supervision of a PhD or professor at the RUG. This case study is performed to fund a foreign excursion for members of the study association T.F.V. 'Professor Francken'. The case study can be something like a theoretical research or a practical assignment. For both the theoretical and practical cases the equipment, infrastructure and knowledge of the university can be used by the students to perform the study. For case studies we enlist students with a Physics, Applied Physics, Mathematics, Applied Mathematics or Astronomy background who are finishing their undergraduate degree or sometimes their graduate degree. In the case of Physics or Astronomy, the student has knowledge of classical and quantum mechanics, and knows how to perform a theoretical study. For Applied Physics, the student has done courses in electronics, mechanics, a basic course in programming and numerical methods. Mathematics and Applied Mathematics students have learned to think analytically and know how to solve problems as such, and know a fair deal about statistics. After enlisting students, we then contact companies who can hire a student for a certain amount of hours, 420 hours for a 'normal' case.

Is your company interested in providing a case study? Please do not hesitate to get in touch and email us on

Available cases

Below are the cases currently available through SLEF. Let us know which ones interest you and do not hesitate to ask any questions you might have. Please bear in mind that a case study may not be suitable as a thesis for your degree programme, since it has to be approved by the relevant Board of Examiners on several criteria (which vary per degree). Negotiations with companies are still ongoing, so please check regularly for new case studies!

Companies are very interested in C++ programmers and have a variety of projects available. If you are interested in a C++ case study, please mail us your CV and field of interests for C++. The companies will then find and shape the project that best suits you. Be sure to mention which C++ courses you have passed, and the professor that taught it.

Case 1: Machine Learning

Superconducting Transition Edge Sensors (TES) represent the state of the art in ultra-sensitive radiation detection, with applications ranging from the far infrared to X-rays. Future instruments will have arrays of many thousands of these detectors and as these arrays grow, so does the time needed to test and characterize them. The fundamental diagnostic for a TES is its current vs voltage curve (IV curve). From the IV curve we can derive important parameters such as the saturation power. The aim of this project is to use machine learning to classify large numbers of IV curves so that they can be analyzed without being inspected by a human. This would save a significant amount of time, especially as arrays become larger. Eventually, we would like to be able to characterize a full array of TES detectors automatically. We have a large collection of IV curves that can be used to train and test machine-learning algorithms, so the project can be done remotely. The project would build on work done by previous students with a view to improving the classification accuracy and exploring alternative approaches.

Case 2: Fourier Transform Spectrometer

The aim of the student project is to characterize and optimize a so-called proto-type Fast-Scan Fourier Transform spectrometer system, optimize the optical throughput of the system, and compare the performance of the instrument with theoretical predictions. The FTS spectrometer system consists of a thermal black body source, a gas cell, the FTS spectrometer, and a cryogenically cooled detector. The operation of an FTS is based on the interference of two optical beams (originally one beam, split into two beams and recombined with a beam splitter within the FTS), where the optical path length of one beam is varied by use of a moving mirror. The movement of the mirror can be continuous (fast-scan,) or in steps (step-scan, step-and-integrate). In a previous student project an existing step-scan Far-infrared Fourier Transform Spectrometer has been modified to include a fast-scan capability (by modifying hardware and software). The framework of the fast-scan mode is now present, but final optimization and characterization.

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The board

Hester Braaksma
Nieske Meindersma
Vice Chairman
Mare Dijkstra
Lidewei Dubbink
Quinten Huisman
External Relations / Event Manager
Frank Pietersen
Goos Mulder
Public Relations
The committee of SLEF 2020
f.l.t.r.: Quinten, Lidewei, Mare, Hester, Nieske, Goos, Frank.