Verkor11d ago

PhD Thesis - Industrial vision system for advanced surface inspection

Grenoble, Auvergne-Rhône-AlpesDoctorat / PhDmid

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Overview

We are opening a new opportunity of PhD within our Process R&D – Automation & Vision system development team. This role is located at the Verkor Innovation Center in Grenoble, France.

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We are opening a new opportunity of PhD within our Process R&D – Automation & Vision system development team.

This role is located at the Verkor Innovation Center in Grenoble, France.

Investigate and compare 3D acquisition principles (stereophotometry, phase-shifting interferometry, vertical scanning interferometry, structured light, and infrared pattern projection) at a fundamental level, assessing their physical limits in terms of resolution, speed, and robustness for various surface characterizations.

Conduct an in-depth study of illumination spectra (visible, NIR, UV, multispectral) and their interaction with various surface properties (reflectance, scattering, translucency of active material coatings) to determine optimal spectral configurations for maximizing defect contrast.

Explore novel image acquisition techniques and optical configurations (multi-angle, multi-wavelength, polarimetric imaging) to capture surface and subsurface information beyond what conventional single-modality systems can achieve.

Design and develop new multimodal deep learning architectures capable of jointly processing heterogeneous data streams (3D topography, 2D intensity, multispectral, and thermal) for 3D reconstruction and defect detection.

Optimize these algorithms specifically for in-line inference: low-latency, high-throughput processing compatible with production line speeds, targeting edge deployment on GPU/FPGA compute platforms.

Address battery-specific AI challenges: extreme class imbalance (rare defects), scarce labeled data (self-supervised, semi-supervised, and synthetic data generation strategies), and generalization across electrode chemistries and process variations.

Benchmark fusion strategies (early, mid-level, late fusion) and quantify the detection gain brought by multimodality versus single-sensor approaches.

Design a real-time data fusion pipeline combining the developed 3D vision system with complementary sensors on the R&D line (line-scan cameras, IR thermography, thickness gauges, laser profilometers).

Collaborate with Process and Equipment teams to prototype and integrate the vision system on the R&D lines.

Build the full acquisition-to-decision pipeline: hardware (cameras, illumination, compute units), software architecture, and data flow (acquisition → preprocessing → fusion → inference → MES feedback).

Evaluate industrial cameras, illumination sources, compute platforms, and software frameworks.

Provide buy-vs-build recommendations for each subsystem.

MSc or Engineering degree in computer vision, optics, image processing, or a related field.

Strong programming skills (Python, C/C++) and experience with deep learning frameworks.

Knowledge of optics, 3D metrology, or acquisition systems is a plus

Fluent English required, French appreciated