MSc Thesis: Visualizing ML Anomalies in Large-Scale Simulators

Saab; Linköpings kommun; On-site; SEK 246,000 - 312,000; Part time

Job summary

Saab in Sweden invites MSc students to apply knowledge to real-world challenges. Your thesis will explore unsupervised ML algorithms, like Isolation Forest and K-means, to identify anomalies in development simulators.

You will work with experienced engineers and gain practical experience while contributing to Saab's advancements. The project includes literature review, interviews with senior developers, and evaluation of models.

Qualifications

• Pursuing a Master of Science and about to start your thesis (30 HP).
• Strong interest in software development and testing.
• Familiarity with ML concepts and anomaly detection is beneficial.

Responsibilities

• Investigate unsupervised ML algorithms for anomaly detection in simulators.
• Review related work and interview Saab engineers.
• Evaluate ML models and structure results for presentation.

Skills

Software development

Software testing

Machine learning

Anomaly detection

Education

Master of Science in Computer Science and Engineering

Master of Science in Industrial Engineering and Management

Master of Science in Information Technology

Job description

Saab in Sweden invites MSc students to apply knowledge to real-world challenges. Your thesis will explore unsupervised ML algorithms, like Isolation Forest and K-means, to identify anomalies in development simulators.

You will work with experienced engineers and gain practical experience while contributing to Saab's advancements. The project includes literature review, interviews with senior developers, and evaluation of models.