Master Thesis: Systematizing Neuro-Symbolic AI for Autonomous Network Management

Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Software Engineering

In short

Ericsson Research is seeking a Master's student for a thesis on systematizing neuro-symbolic AI for autonomous network management. The role involves conducting a systematic literature review to understand the landscape, identify applications in networking, and map research and standardization gaps.

Responsibilities

Conduct a systematic mapping and systematization of knowledge on neuro-symbolic AI.
Investigate existing research landscape and develop a structured understanding of the field.
Develop a taxonomy and knowledge structure derived from existing research and relevant standards.
Review and classify relevant research.
Analyze applicable standards.
Document findings in a Master's thesis.

Requirements

Enrolled in a Master's programme in Computer Science, Cybersecurity, Machine Learning, or an equivalent field.
Solid software-development experience.
Interest in one or more of the following areas: neuro-symbolic AI, large language models, autonomous systems, automation, or security.
Strong analytical, research, and technical writing skills.

Desired Qualifications

Experience with systematic literature reviews is considered a plus.
Relevant project experience is highly valued.
Technical reports, such as school assignments or blog posts, may also be included as supporting material.

Benefits

Outstanding opportunity to use skills and imagination to push boundaries.
Build solutions never seen before.
Be challenged, but not alone.
Join a team of diverse innovators.
Opportunity to craft what comes next.

Skills

Machine LearningNetwork SecurityNeuro-symbolic AILarge Language ModelsAutonomous SystemsAutomationSecuritySoftware DevelopmentSystematic Literature ReviewTechnical Writing

#AI#Machine Learning#Neuro-Symbolic AI#Autonomous Systems#Network Management#Master Thesis

About Ericsson

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