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Werkstudent: Mathematik, Statistik & ML Metrologie

Remote / Online - Candidates ideally in
Germany, Pike County, Ohio, USA
Listing for: dogado GmbH
Full Time, Apprenticeship/Internship, Remote/Work from Home position
Listed on 2026-05-12
Job specializations:
  • Research/Development
    Research Scientist, Data Scientist, Mathematics
Job Description & How to Apply Below
Position: Werkstudent: Mathematik, Statistik & ML in der Metrologie
Location: Germany

Werkstudent
* in

Mathematik, Statistik, Scientific Computing

Ihr Profil:

The art of measurement — made in Germany. Striving to perfect it is the mission of the 2,100 employees of PTB, the Physikalisch-Technische Bundesanstalt. As Germany’s national metrology institute and a leading center of research, we operate in an international environment to develop world-class measurement standards. We at PTB work to ensure that people and organizations can trust the measurements they use.

At our Berlin-Charlottenburg site, we are looking to fill the following position in Department 8.4 (Mathematical Modelling and Data Analysis):

Working student
Mathematics, Statistics, Scientific Computing

Virtual experiments are being used more frequently in metrology and can support data analysis and uncertainty evaluation in complex applications. However, the usually deterministic and purely parametric formulation of virtual experiments often leads to modelling errors in high-dimensional and high-precision applications in metrology. Working Group 8.42 "Data Analysis and Measurement Uncertainty" has developed an approach that incorporates local Gaussian random fields in order to reduce modelling errors and enable uncertainty evaluation.

We are looking for support for the further development of the statistical approaches, the application to practical examples from metrology, and the efficient (scalable) implementation of Bayesian inference. Your activities will include:

  • Development of a method for the automatic identification of 2D subsets, based on correlations, for a local Gaussian random field approach
  • Theoretical and practical analysis of the developed statistical inference method using a metrological application
  • Implementation of the developed methods in R or Python
  • Extension of the method to other realistic applications in metrology, with the possibility to focus in the direction of machine learning

Your profile:

  • You are enrolled in a bachelor’s or master’s degree programme in mathematics, statistics, scientific computing or a comparable subject
  • It is an advantage if you have experience in Bayesian analysis and inverse problems
  • You are interested in theoretical / mathematical method development and application to real problems
  • You have experience in R and/or Python
  • You have excellent teamwork and communication skills
  • Valuable practical experience in a leading metrology institute to complement your studies
  • Flexible working hours adapted to your studies and the opportunity to work from home
  • Employment for an initial period of 6 months with up to 60 hours/month (maximum length of until graduation/disenrollment)
  • Holiday entitlement and continued payment of sick pay
  • Very good public transport connections
  • Free parking for cars, motorbikes and bicycles as well as charging facilities for e-bikes
  • Canteen on the premises
  • Possibility to write a bachelor's or master's thesis in this field

PTB promotes gender equality and strongly encourages applications from female candidates. At the same time, we strive to reflect the diversity of our society. We therefore welcome every application submitted, regardless of the candidate’s gender, cultural or social background, religion, ideology or sexual identity. If equally suited to the position, disabled persons or persons having equivalent status under German law will be given preference.

We look forward to receiving your application by 23 February 2026 under . 26-01-8C. Please click on the following button: ONLINE BEWERBEN. This will directly lead you to our application portal where you can upload your documents (CV, certificates, Cover letter). Unfortunately, we cannot accept applications sent via email. With your application you accept the data protection regulations.

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