Master’s Thesis, 30-45 HP: Scientific Machine Learning for Physics-Informed Inverse Problems in SAR imaging
Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Software Engineering · Data Science
In short
This Master's Thesis project at Saab in Solna, Sweden, focuses on developing high-performance computing (HPC) simulation tools using Scientific Machine Learning (SciML) for Physics-Informed Inverse Problems in Synthetic Aperture Radar (SAR) imaging. The project aims to address ill-posedness in SAR imaging by integrating learned algorithms with physical laws, requiring strong programming skills in frameworks like PyTorch or JAX. Suitable for 1-2 master's students nearing completion of their program.
Responsibilities
- Develop high-performance computing (HPC) simulation tools from SciML.
- Integrate learned algorithms with physical laws and domain knowledge.
- Address issues in ML related to model accuracy, efficiency, and interpretability.
- Develop reconstruction methods with significantly better performance.
- Facilitate large scale forward simulations.
- Aid in developing novel methods for large-scale data-driven inverse problems based on SciML.
Requirements
- Student at the end of their Master’s program.
- Interest in scientific computing, applied physics/mathematics, and machine learning.
- Strong programming skills.
- Familiarity with common machine learning frameworks, such as PyTorch and/or JAX.
- Ability to communicate efficiently both orally and in writing.
- Ability to work independently and as part of a dynamic team.
- Must pass a security vetting.
Desired Qualifications
- Background in computer science, machine learning, applied mathematics, statistics, physics or any related field.
- Familiarity with GPU programming is highly advantageous.
Benefits
- Opportunity to collaborate with experienced engineers and specialists.
- Gain invaluable practical experience.
- Make a tangible contribution to company growth and development.
- Support and guidance to translate theoretical knowledge into practical solutions.
- Become a driving force behind Saab's technological advancements.
#scientific machine learning#physics-informed#inverse problems#SAR imaging#high-performance computing#machine learning#applied mathematics#physics#computer science#statistics
Company
Saab
Job Posted
1 month ago
Expires
in 1 week
Employment Type
Internship
WorkMode
On Site
Experience Level
Entry
Locations
Solna, Sweden
Qualification
Master
Applicants
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