A
Engineering Internship - Deep Learning for Infrared Thermography Antenna Measurements
Contract type
One-time
Work mode
Remote · Toulouse, France
Experience
Junior / entry level · Not stated
Level inferred from job title
Job description
Six-month internship at ANYFIELDS developing physics-driven neural networks to restore infrared thermography antenna field maps, working with the Innovation team in Toulouse.
At a glance
- Employment
- Internship
- Work mode
- Remote · Toulouse, France
What you'll do
- Benchmark synthetic and measured datasets and reproduce the conventional methods (wavelet denoising, drift removal, deconvolution, slanted edge)
- Estimate the PSF of the detector with a neural network constrained by the film heat diffusion and the optics, estimated from a few measurements; explain the gap between the theoretical (about 1 mm) and measured (4 to 8 mm) resolution; compare with conventional methods
- Implement denoising by self-supervised deep denoising of the maps, quantify the gain in dB towards 35 to 40 dB, and rank the limiting factors of the setup
- Validate by test whether the imaging resolves the individual elements of array antennas in the Ku and Ka bands, before and after improvement; report on the retained methods
What we're looking for
- Bac+5 - Engineering school / Master in applied mathematics, signal and image processing, machine learning and/or electromagnetics
- Programming skills (preferably Python), experience with a deep learning framework
- Team spirit, proactive attitude and good communication skills in an interdisciplinary team
Nice to have
- Knowledge of inverse problems or infrared cameras
Your team
Innovation team
Apply
About ANYFIELDS
ANYFIELDS measures antennas by infrared thermography: a thermosensitive film heated by the radiated field is imaged by an infrared camera, giving a 2D map of the electric field, nonintrusive and very close to the antenna.