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Master thesis

Probabilistic machine learning for asset inspection



To join our team in Science Disciplines, we are looking for a student on the topic:

Probabilistic machine learning for asset inspection 

Safe operation of industrial assets requires regular inspection and assessment of an asset’s condition. Inspections often use indirect imaging technologies that can’t measure the condition of an asset directly. For example, corrosion causes magnetic flux leakage, such that changes in magnetic flux signal the presence of corrosion. Yet, such indirect measurements can be ambiguous, for example if different corrosion patterns yield the same magnetic flux measurement. This can have important consequences when one corrosion pattern will cause a failure, but others will not. The goal of this thesis is to provide uncertainty assessments around an asset’s condition by providing all possible patterns that fit the measured data.
This thesis is being announced in cooperation with Prof. Dr. Martin Atzmüller, Osnabrück University​.
Thesis Challenges:
  • Combining deep-neural networks with probabilistic modeling.
  • Implementation and modification of existing deep-neural networks in a probabilistic inference framework
  • Evaluation of the precision and speed of the new framework


To become part of the ROSEN family, you convince with your ability to work in a team and are used to working independently. Moreover: 
  • Master's student in Computer Science, Cognitive Science or similar fields
  • Interest in machine learning and statistics beyond deep-neural networks
  • Good coding skills in python
  • First experience with Deep Learning frameworks (e.g. pytorch or tensorflow)
  • First experience with probabilistic modelling (e.g. Stan or pymc3 or pyro or other)
  • Interest in probabilistic modelling and uncertainty estimation

Our Offer

We offer insights into the work of an international, innovative and long-term oriented group of companies. In an open corporate culture with fast decision-making processes, you can successfully implement your ideas. We will also support you in the following areas as part of your final thesis:
  • Know-how development in the mentioned topics
  • Individual supervision and independent work
  • Exchange with other students
  • Invitation to exclusive ROSEN events


is a leading privately owned company that was established in 1981. Over the last 4 decades, ROSEN has grown rapidly and is today a worldwide technology group that operates in more than 120 countries with almost 4000 employees.

ROSEN offers sophisticated and highly innovative products and services to the oil and gas and other engineering industries. ROSEN is an extended team of people with a passion for technology and innovation. We are always looking for young professionals as well as experienced employees.

Our ongoing organic growth results in career opportunities and gives our employees chances for further development and added experience.

For more information about ROSEN go to www.rosen-group.com.


Annika Knurr
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