Master internship: Uncertainty-Aware Video Processing for Structural Health Monitoring
Inria · Rennes
Research instituteonsiteintern
At a glance
Highlights
- Extract motion signals at thousands of points from video for structural monitoring.
- Quantify measurement reliability from noisy high-dimensional video data.
- Validate uncertainty and dimensionality reduction methods on experimental data.
Ideal candidate
Motivated M2 student with strong applied-math mindset who enjoys turning noisy data into reliable insights and applying algorithms to real-world structural monitoring challenges.
Requirements
- Master's (M2) or final-year engineering student
- Background in applied mathematics, signal processing, statistics or related field
- Interest in developing algorithms for real-world problems
- Programming experience in Python, MATLAB, Julia or equivalent
- Good English communication skills
Lab profile
About Inria
French national research institute advancing digital sciences, computing, AI and applied mathematics.
What they build
- Digital sciences and computing research
- Artificial intelligence for microscopy and video analysis
- Quantum information theory
Known for
- Joint teams with Paris-Saclay University and Institut Polytechnique de Paris
- Embedded in Paris-Saclay science and technology cluster
- Rich R&D ecosystem with startups, industry and clusters
- International collaborations and multinational scientific staff
Key facts
- Founded in 1967
- Headquartered in France
- Nine research centres across France
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