Master Thesis, 30HP: Finding the UAV in a Haystack of Birds - Deep Models for Target Classification in Radar Tracking (Deep Learning/Radar)

Location: Göteborg, Sweden

Company

hirify.global is a defense and security company developing advanced systems in aeronautics, weapons, command and control, sensors, and underwater systems.

What you will do

• Develop Bayesian methods for classifying radar targets as birds or unmanned aerial vehicles.
• Exploit behavioral differences between birds and UAVs for automatic target classification.
• Investigate likelihood-based classification using learned system models.
• Explore traditional kinematic models, deep latent-space models, and hybrid models.
• Study system identification and filters for likelihood evaluation within a modest computational budget.
• Collaborate with experienced engineers and specialists while completing the thesis project.

Requirements

• Be in the final stage of a technical master's degree in Engineering Physics, Engineering Mathematics, Electrical Engineering, Automation and Mechatronics, or a similar field.
• Have an interest in advanced mathematics and numerical methods.
• Advanced mathematics coursework, particularly Bayesian statistics, is beneficial.
• Practical experience with deep learning is beneficial.
• The project is suitable for one or two students.
• Pass security vetting under current security-protection regulations; additional citizenship obligations may apply for positions requiring security clearance.

Culture & Benefits

• Work with experienced engineers and specialists on practical defense and security technology.
• Receive support and guidance to translate theoretical knowledge into practical solutions.
• Contribute to technology intended to help keep people and society safe.
• Gain practical experience in an innovative engineering environment.