Master’s Thesis, 30-45 HP: Scientific Machine Learning For Physics-Informed Inverse Problems In SAR Imaging (AI)

TL;DR

Master’s Thesis, 30-45 HP: Scientific Machine Learning for Physics-Informed Inverse Problems in SAR imaging (AI): Developing HPC simulation tools and reconstruction methods for SAR imaging using SciML with an accent on solving ill-posed inverse problems. Focus on integrating physical laws with learned algorithms to improve model accuracy, efficiency, and interpretability in radar wave imaging.

Location: Solna, Sweden

Company

hirify.global is a leading defence and security company that designs, manufactures, and maintains advanced systems in aeronautics, weapons, command and control, sensors, and underwater systems.

What you will do

• Develop high-performance computing (HPC) simulation tools based on Scientific Machine Learning (SciML) for electromagnetic wave scattering.
• Address ill-posed inverse problems to improve reconstruction methods for Synthetic Aperture Radar (SAR) imaging.
• Create frameworks to facilitate large-scale forward simulations of radar wave imaging.
• Utilize modern tools from numerical analysis, high-performance computing, and machine learning.
• Collaborate with specialists in the Future Technologies EW and Systems group to build novel data-driven inverse problem methods.

Requirements

• Currently at the end of a Master’s program and eligible to start a 30-45 HP thesis.
• Strong foundation in Computer Science, Machine Learning, Applied Mathematics, Statistics, or Physics.
• Strong programming skills and familiarity with ML frameworks such as PyTorch and/or JAX.
• Must pass a security vetting based on current security protection regulations.
• Additional obligations on citizenship may apply for security clearance.
• Ability to communicate efficiently both orally and in writing.

Nice to have

• Familiarity with GPU programming.

Culture & Benefits

• Opportunity to apply theoretical academic knowledge to real-world technological breakthroughs in defense.
• Collaboration with experienced staff engineers, specialists, and researchers.
• Support and guidance to translate academic rigor into practical solutions.
• Exposure to cutting-edge research in electronic warfare and intelligent sensor systems.