Steinbuch Centre for Computing (SCC)

Job opportunities

At SCC you work in an innovative organisation with an excellent reputation; an organisation in the middle of international technological developments that helps accellerating science. If you wish to set ambitious goals, find freedom and flexibility in your work and continue to develop your personal strengths, then a job at SCC is just the thing for you.

We are always happy to receive your application, even if currently no vacancies are listed, a job opening for researchers, administrators, scientific supporters is always around the corner.

Are you interested in working with us? Then send your speculative application to: personal∂scc.kit.edu

Students interested in working as a research assistant or looking for a topic for their master or bachelor thesis are also welcome. Theses can be supervised primarily in computer science or mathematics, but we also have good contacts to other KIT faculties.

SCC

The Steinbuch Centre for Computing (SCC) is the Information Technology Centre of KIT. We work in a wide variety of projects with universities, research institutions and companies, both nationally and internationally. Topics range from the analysis of large scale data to data-intensive computing and cloud computing to parallel and numerical methods. We develop and operate innovative IT services as well as large research facilities.

Overview

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Jobs at SCC

Currently there are no job offers via the Job Portal of KIT however, you may find further job offers at the bottom of this page, and we always welcome your initiative so do send us your resume.

Offers for Students

  1. Thesis: Lossless Compression of Climate Data using Machine Learning (m/f/d)
    The aim of this thesis is to develop a prediction-based compression algorithm. Here, the datapoints in the dataset are traversed individually and a prediction for the current value is made. Afterwards the difference (also called residual) between the prediction and the true value is calculated. This difference is finally encoded and stored on disc.  With the help of the prediction method, the traversing strategy and the residual, the data can be reconstructed without any loss. The more accurate the prediction, the smaller the difference and thus the final filesize will be. Machine Learning methods can help in the development of new traversing strategies and better prediction methods.
     
  2. The Department DEM has various offers for theses, doctorates and positions for research assistants.
     
  3. Student Research Assistant: The Department SCM offers a job in the domain of uncertainty quantification in radiation therapy. For more information see Job offer.
     
  4. Research assistants welcome: Offers in the department SCS