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Master Thesis, 30 HP: Visualization of big data from ML-based anomaly detection in simulators

Teknik, data och digitalt · Data, AI och analys · Datavetenskap · Mjukvaruutveckling · Datavisualisering

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I korthet

This Master Thesis project at Saab focuses on visualizing big data from ML-based anomaly detection in simulators. Students will apply unsupervised ML algorithms like Isolation Forest and K-means to identify problems in complex systems and present the results effectively, collaborating with experienced engineers.

Ansvarsområden

  • Investigate how unsupervised ML algorithms can be used to identify problems within simulators of large-scale, complex systems.
  • Structure and present the results of ML-based anomaly detection.
  • Conduct a review of related previous work.
  • Conduct interviews with senior software development engineers at Saab Aeronautics.
  • Evaluate using one or several ML models relevant to anomaly detection.

Krav

  • Student at the end of Master of Science in Computer Science and Engineering, Industrial Engineering and Management, or Information Technology.
  • Interest in software development and software testing.
  • Ability to pass a security vetting.
  • Interest in machine learning algorithms (Isolation Forest, K-means).
  • Interest in data visualization.

Önskade kvalifikationer

  • Experience with ML models relevant to anomaly detection.
  • Familiarity with big data visualization techniques.

Förmåner

  • Opportunity to apply theoretical knowledge and fresh perspectives to real-world challenges.
  • Collaborate with experienced engineers and specialists.
  • Gain invaluable practical experience.
  • Make a tangible contribution to Saab's growth and development.
  • Support and guidance to translate theoretical knowledge into practical solutions.
#thesis#master thesis#big data#machine learning#anomaly detection#simulators#visualization#software development#software testing
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Företag

Saab

Publicerade jobb

för 1 vecka sedan

Upphör

om 1 månad

Anställningstyp

Praktik

Arbetsform

På plats

Erfarenhetsnivå

Junior

Platser

Linköping, Sweden

Kvalifikation

Masterexamen

Sökande

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