Internship Scalable Local Inversion for Real-Time Ultrasonic Imaging-Saclay-H/F

CEA; Saclay; On-site; EUR 8,900 - 13,000; Full time

Job summary

CEA's LIIDE laboratory in Saclay is seeking an intern to develop a physics-informed local inversion for ultrasonic imaging that scales to extended inspection areas while aiming for real-time operation. You will study reusable structures across neighboring operators, work on overlapping reconstruction stitching, and explore parameter transfer across windows, with exposure to state-of-the-art equipment and a collaborative research environment.

The internship may lead to a scientific publication.

Qualifications

• Final-year master's student or engineering student in applied mathematics, signal processing or scientific computing.
• Strong Python programming and numerical optimisation skills.
• Experience with PyTorch and ultrasonic imaging is a plus.

Responsibilities

• analyse the spatial regularities and the low‑rank or spectral structure of local operators;
• design overlap and stitching strategies for neighbouring reconstruction windows;
• investigate parameter-transfer rules across windows;
• optimising the implementation.

Skills

Python programming

Numerical optimisation

Inverse problems

Signal processing

Education

Master's degree / final-year student in applied mathematics or related field

Tools

PyTorch

GPU computing

Parallel computing

Job description

Internship Scalable Local Inversion for Real-Time Ultrasonic Imaging-Saclay-H/F

Category

Instrumentation, metrology and control

Contract

Internship

Job title

Internship Scalable Local Inversion for Real-Time Ultrasonic Imaging-Saclay-H/F

Subject

The internship aims to make a physics-informed local inversion method for ultrasonic imaging scalable to extended inspection areas and compatible with real‑time operation. The work will address the structure of neighbouring local operators, the stitching of overlapping reconstruction windows, the transferability of learned parameters, and implementation efficiency. As an intern at the CEA, you will have the opportunity to work within a world‑renowned research environment. Our teams consist of passionate and dedicated experts, providing an ideal setting for learning and collaboration. You will have access to state‑of‑the‑art equipment and top‑tier research resources to carry out your assignments. The work conducted may potentially lead to a scientific publication.

Context :

Ultrasonic imaging from Full Matrix Capture data can exceed the resolution of the Total Focusing Method (TFM) when the individual transmitter‑receiver contributions are inverted locally.

Local linear direct model

The current physics‑informed unrolled method [1] can resolve point reflectors below the Rayleigh limit. The learned inversion parameters can also transfer across nearby depths.

Two point‑like reflectors separated by 0.8 mm (left) and 0.4 mm (right). Top: TFM images. Middle: reconstructions obtained at inference with configuration B. Bottom: lateral profiles at z = 16 mm. Blue crosses and dotted lines indicate the reflector positions.

However, the method currently processes isolated windows and requires the computation of large local operators.

Extending this approach to whole‑component inspection requires a scalable strategy that preserves reconstruction quality while meeting real‑time constraints.

The objective of the internship is to develop a scalable implementation of local ultrasonic inversion for extended inspection areas. The work will focus on identifying reusable structures across neighbouring operators, combining overlapping local reconstructions consistently, and determining how far locally learned parameters can transfer before retraining becomes necessary.

The internship work will include:

• analysing the spatial regularities and the low‑rank or spectral structure of local operators;
• designing overlap and stitching strategies for neighbouring reconstruction windows;
• investigating parameter‑transfer rules across windows;
• optimising the implementation.

[1] K. Diallo, F. M. Ngolè Mboula and F. Le Bourdais, “Physics‑Informed Super‑Resolved Ultrasonic Imaging,” 11th Junior Conference on Data Science and Engineering, 2026 [ Online ].

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Methods / Means

FMC ultrasonic data; Algorithm unrolling; PyTorch; parallel and GPU computing

The internship is intended for a final‑year Master’s student or engineering student specialising in applied mathematics, signal processing or scientific computing.

The candidate should have strong Python programming and numerical optimisation skills. Experience with PyTorch, inverse problems, GPU programming or ultrasonic imaging would be an advantage.

Site

Saclay

Location

Saclay

PhD opportunity

Non

Requester

01/03/2027

General information

Organisation: The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas : defence and security, nuclear energy (fission and fusion), technological research for industry, fundamental research in the physical sciences and life sciences. Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners. The CEA is established in ten centers spread throughout France.

Reference

2026-42210

The Intelligent, Distributed and Embedded Instrumentation Laboratory (LIIDE) develops an integrated hardware and software platform for designing the capabilities of future instrumentation systems. The laboratory focuses jointly on: 1. Hardware solutions consisting of versatile, modular electronic boards and the software required to operate them, supporting a broad range of sensor technologies. 2. Innovative artificial intelligence capabilities for distributed measurement and resource‑efficient, distributed learning.