Master Thesis: Antenna System and Technology

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

In short

Master Thesis project focused on using machine learning to improve antenna beam patterns in wireless networks by uncovering optimal excitation vectors, considering effects like mutual coupling. The project involves analyzing correlations, developing a model, and validating it with data and measurements.

Responsibilities

Analyze the interaction between beam weights and antenna system performance, focusing on aspects such as side-lobe suppression.
Examine the correlation between cost functions and excitation vectors across various antenna geometries.
Investigate the influence and dependencies between excitation vectors and cost functions.
Develop an optimized excitation-vector model.
Assess the model’s effectiveness using established quality metrics from both machine learning and antenna design.
Validate the model through measurement data.

Requirements

Currently enrolled in a Master's program in Engineering Physics, Electrical Engineering, Computer Engineering, or an equivalent field.
Knowledge of electromagnetic field theory.
Experience with Python programming.
Experience with MATLAB.
Experience applying machine learning methods.
An analytical and structured approach to problem-solving.

Desired Qualifications

This thesis integrates antenna theory, electromagnetic modeling, optimization methods, machine learning, and measurement-based validation.

Benefits

Outstanding opportunity to use skills and imagination to push the boundaries of what's possible.
Build solutions never seen before to some of the world's toughest problems.
Be challenged, but not alone; join a team of diverse innovators.
Be part of a culture that goes beyond the status quo to craft what comes next.
Encouraging a diverse and inclusive organization is core to our values.
Championing diversity and inclusion in everything we do.
Collaborating with people with different experiences drives innovation.
Be part of Ericsson's future growth.
Encouragement for people from all backgrounds to apply and realize their full potential.

Skills

PythonMATLABMachine LearningElectromagnetic Field Theory

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About Ericsson

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