Engineering Internship - Deep Learning for Infrared Thermography Antenna Measurements
ANYFIELDS has an opening for an Engineering Internship - Deep Learning for Infrared Thermography Antenna Measurements in Toulouse, France. The listing describes it as a full-time, internship position.
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Our own short read of this listing, built only from the facts it gives. The employer’s original text follows further down.
ANYFIELDS has an opening for an Engineering Internship - Deep Learning for Infrared Thermography Antenna Measurements in Toulouse, France. The listing describes it as a full-time, internship position.
The advert mentions Python, machine learning and deep learning among the skills and tools for this role.
The employer does not state a salary in this listing; DGJ Insight below shows an official pay benchmark for the place where one exists.
Visa sponsorship is not mentioned. Applicants from outside France should check the official work permit route before applying.
Dev Global Jobs found this job on Arbeitnow on Nov 4, 2026.
- Employer
- ANYFIELDS
- Location
- Toulouse, France
- Job type
- Full-time
- Level (from the title)
- internship
- Pay
- Not stated by the employer
- Found
- Nov 4, 2026 on Arbeitnow
- Employer text
- 311 words, about 1 min to read
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DGJ Insight
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About the role
Full text from the employer, as published on Arbeitnow, arranged into sections. Nothing added or removed.
01THE POSITION
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. Two limits remain: the maps are noisy (dynamic range of 25 to 30 dB at best, 35 to 40 dB needed to retrieve side lobes and cross-polarization), and they are blurred by the response of the detector (film and optics), whose resolution is not explained by the theory.
This internship develops physics-driven neural networks, trained without any clean reference, to restore the maps, and compares them rigorously with the conventional methods already implemented.
Missions :
Benchmark synthetic and measured datasets, reproduction of the conventional methods (wavelet denoising, drift removal, deconvolution, slanted edge).
Estimate PSF of the detector: 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, quantified gain in dB towards 35 to 40 dB, ranking of 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.
You will work at the crossroads of electromagnetics, imaging and deep learning, with the engineers of the Innovation team.
Location: Toulouse (city centre)
Start: As soon as possible
Duration: 6 months
02Profile
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
Knowledge of inverse problems or infrared cameras is a plus
Team spirit, proactive attitude and good communication skills in an interdisciplinary team
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