Become a Master Lab researcher in SmallData, running from February 10 to April 17, 2025

Apply until December 12, 2024!

SMART Master Lab

SmallData brings together a broad group of data disciplines from computer science, mathematics, statistics and systems modeling, and biomedicine to address small data challenges that lie at the intersection of these disciplines. 

SmallData offers a unique opportunity to establish a shared language across all disciplines and to cross disciplinary boundaries through interdisciplinary training and collaboration.

Here you will find everything you need to know to start your journey towards achieving your academic goals.

As a Master Lab researcher within SmallData, you will:

  • Work full-time for about eight weeks on a research project mentored by the early career researcher in the research group of the respective principal investigator
  • Benefit from a qualification program tailored to the topics of SmallData
  • Carry out collaborative interdisciplinary research through our network structure
  • Learn developing your own research questions and designs
  • Have the opportunity to directly continue with your Master's thesis project

Admission criteria

We expect you to:

  • Be enrolled to a master's program in a relevant field such as computer science, (bio)statistics, mathematics, physics, engineering, life sciences, or other related disciplines at a German University / German Hochschule
  • Have strong intrinsic motivation to work in interdisciplinary projects and to indicate why you are a good fit for the program         
  • Possess intermediate to advanced programming skills
  • Commit full-time, ideally on-site, throughout the semester break
  • Have a very good command of written and spoken English.

Preference will be given to:

  • Applicants from the University of Freiburg
  • Applicants who demonstrate strong programming skills, and a proven track record in research methodologies.
  • Applicants with a high level of motivation and passion for research, showing their readiness to excel in a dynamic academic environment.

Application

To make the application process as simple as possible, all relevant information is collected via an application form that you can access by clicking on the button below. It is important that you take the time to complete the form accurately and in English only. Only complete applications will be considered. Application deadline: December 12th, 2024.

The application form includes:

  • your ranked list of up to three preferred research projects and corresponding supervisors
  • your personal details and university education
  • your research interests in SmallData through a letter of motivation
  • your technical skills and research experience
  • your approach to research

  

 

 

 

 

Program details

Stage 1:
Application and selection

Submit your data via the application form until December 12th, 2024. After submitting the fully completed form, you will automatically receive a confirmation email.
Related principal investigators and early career researchers will review the applications and select suitable candidates.

Stage 2:
Introduction phase

Selected candidates start with workshops on small data methodologies including hands-on applications. They join their assigned labs to familiarize themselves with the lab. They exchange experiences, accompanied by a social activity to build connections. 

Start Date: February 10, 2025

Stage 3:
Working phase

Master's students will embark on hands-on research training, developing cutting-edge small data methodologies to advance their projects. They will have the opportunity to showcase their progress, tackle challenges, and receive expert guidance to refine their work and drive success.

Stage 4:
Final presentation

By the end of the program, students will present their Master Lab project outcomes to SmallData members, showcasing their work and insights.

Closing date: April 17th, 2025

Contact

Your contact for questions regarding the application process:

Administrative Manager

Marc Schumacher

Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center –
University of Freiburg