Master Thesis, 30 hp: Testing and simulation for collaborative AI systems
Technology, Data & Digital · Data, AI & Analytics · Artificial Intelligence · Data Science · Software Engineering
In short
This Master Thesis project at Saab in Linköping, Sweden, focuses on developing testing and simulation frameworks for collaborative AI systems, with a focus on autonomous vehicles. The project aims to address the challenges of validating multi-agent systems and bridging the gap between simulation and real-world deployment.
Responsibilities
- Design and implement a comprehensive testing and simulation infrastructure for collaborative multi-agent AI systems.
- Handle different decision-making architectures (centralized, consensus-based, distributed).
- Implement and demonstrate the framework in a simulated environment and potentially the Visionen arena at LiU.
- Collaborate with experienced engineers and specialists.
- Gain practical experience in AI and autonomous systems.
Requirements
- Student eager to apply theoretical knowledge to real-world challenges.
- Master's level student.
- Understanding of autonomous systems, multi-agent coordination, and AI.
- Familiarity with simulation environments.
- Ability to pass security vetting.
Desired Qualifications
- Experience with collaborative AI systems.
- Knowledge of different decision-making architectures (centralized, consensus-based, distributed).
- Experience with autonomous vehicle applications.
- Familiarity with the Visionen arena at LiU.
Benefits
- Opportunity to work on cutting-edge technology.
- Gain invaluable practical experience.
- Make a tangible contribution to company growth and development.
- Support and guidance to translate theoretical knowledge into practical solutions.
#AI#autonomous systems#simulation#testing#collaborative AI#multi-agent systems#master thesis#internship
Company
Saab
Job Posted
14 hours ago
Expires
in 1 month
Employment Type
Internship
WorkMode
On Site
Experience Level
Entry
Locations
Linköping, Sweden
Qualification
Master
Applicants
Be an early applicant