Physics-Informed ML for High-Res Pedestrian Radar Imaging

Imec; Vlaams-Brabant; On-site; EUR 12,000 - 18,000; Full time

Job summary

Imec invites applications for a Physics-Informed Machine Learning internship focused on radar imaging of pedestrians. You will work on a FMCW/MIMO ISAR processing framework, exploring physics-informed and deep-unfolding approaches to improve autofocus and image reconstruction.

The position targets MSc or PhD students in electrical engineering, computer science, or related fields, with Python and ML experience, and a strong interest in radar imaging and computational imaging.

Qualifications

• Pursuing MSc or PhD in electrical engineering, telecommunications, computer science, AI, signal processing, or related field.
• Strong interest in radar signal processing, machine learning, or computational imaging.
• Experience with Python and preferably PyTorch.

Responsibilities

• Familiarize yourself with FMCW/MIMO radar processing, range-Doppler processing, tracking, and ISAR image formation.
• Process and analyse measured radar data from pedestrians performing different motions.
• Develop ML methods that improve autofocus, motion compensation, or image reconstruction.
• Validate algorithms on experimental pedestrian radar measurements.

Skills

Python

PyTorch

Radar signal processing

Machine learning

English (written/spoken)

Education

MSc/PhD in electrical engineering or related

Tools

PyTorch

NumPy/SciPy

MATLAB

Job description

Imec invites applications for a Physics-Informed Machine Learning internship focused on radar imaging of pedestrians. You will work on a FMCW/MIMO ISAR processing framework, exploring physics-informed and deep-unfolding approaches to improve autofocus and image reconstruction.

The position targets MSc or PhD students in electrical engineering, computer science, or related fields, with Python and ML experience, and a strong interest in radar imaging and computational imaging.