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

Are you a student eager to apply your theoretical knowledge and fresh perspectives to real-world challenges? At Saab, we believe that innovation thrives on new ideas, and your master thesis project could be the spark that ignites our next technological breakthrough.

Your role

We recognize the immense value that students bring to our company. Your academic rigor, combined with your enthusiasm for cutting‑edge technology, allows you to approach problems with a unique and insightful lens. At Saab, you’ll have the opportunity to collaborate with experienced engineers and specialists, gaining invaluable practical experience while making a tangible contribution to our growth and development.

Background

Isolation Forest and K‑means are popular unsupervised machine learning algorithms used for anomaly detection, capable of identifying outliers or anomalies in datasets generated through logging or recording. Threshold levels are critical in determining whether an identified anomaly indicates an actual problem: a lower threshold produces a higher number of events flagged as anomalies, requiring more extensive manual post‑analysis.

Description Of The Thesis Project

This MSc thesis project aims to investigate how unsupervised ML algorithms can be used to identify problems within simulators of large‑scale, complex systems, and how the results can best be structured and presented. The study will include a review of related previous work, interviews with senior software development engineers at Saab Aeronautics, and an evaluation using one or several ML models relevant to anomaly detection.

Team Rigs and Integration are responsible for the overall integration of our Development Simulators and offers a unique opportunity to gain insight in how a complex aircraft system works. We work in close cooperation with our stakeholders and with teamwork, innovation and curiosity we develop the simulators of today and tomorrow.

Your profile

his Master Thesis is suitable for students with interest in software development and software testing. You are at the end of your Master of Science in e.g. Computer Science and Engineering, Industrial Engineering and Management, or Information Technology and about to start your Master Thesis work for 30 HP

We provide the support and guidance you need to translate your theoretical knowledge into practical solutions. Join us and become a driving force behind Saab’s technological advancements!

This position requires that you pass a security vetting based on the current regulations around/of security protection. For positions requiring security clearance additional obligations on citizenship may apply.

Kindly observe that this is an ongoing recruitment process and that the position might be filled before the closing date of the advertisement.

Contact information

Martin Ling, Manager
073-418 4028
[e-mail]

Torvald Mårtensson, Master Thesis Supervisor
073-418 2761
[e-mail]

What you will be a part of

Explore a wealth of possibilities. Take on challenges, create smart inventions, and grow beyond. This is a place for curious minds, brave pioneers, and everyone in between. Together, we achieve the extraordinary, each bringing our unique perspectives. Your part matters.

Saab is a leading defense and security company with an enduring purpose, to help nations keep their people and society safe. Empowered by its 28,000 talented people, Saab constantly pushes the boundaries of technology to create a safer and more sustainable world.

Saab designs, manufactures and maintains advanced systems in aeronautics, weapons, command and control, sensors and underwater systems. Saab is headquartered in Sweden. It has major operations all over the world and is part of the domestic defense capability of several nations. Read more about us here.