Master Thesis Intern AI & Security

About This Opportunity

You will be joining Ericsson as a Master Thesis Intern within the Product Security Assurance team. As such you will be working with experts in security assurance that work across the entire Ericsson portfolio. The aim of the thesis project will be to research and experiment with utilizing GenAI to supplement penetration testing in the context of product security. The specific direction and methodologies for the thesis project will be defined together with the student.

You should be in your final year in Cyber Security, Computer Science, Computer Engineering, Machine Learning, or similar

The Skills You Bring

• Proficiency and experience in Generative AI, and Machine Learning models
• Good understanding of applied computer security
• Programming skills
• Self-starter mentality
• Curiosity and a strong desire to learn
• Fluent in English
  
  

Note: The selected candidate will need to go through mandatory security vetting.

Interns:

Interns who join us will enjoy an outstanding chance to make connections, to make change, to make a real difference. We are always looking for interns to become permanent members of our Ericsson team, so you’ll have the opportunity to discuss your future with us during your internship.

What happens once you apply?

Click here to find all you need to know about what our typical hiring process looks like. This may vary depending on the location and role.

Frequently asked questions

Students and Early Careers

Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we nurture it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team.

Ericsson is proud to be an Equal Opportunity and Affirmative Action employer, learn more.

Primary country and city: Finland (FI) || Jorvas

Req ID: 757936

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