Research Intern

Vizzia

. Conduct a literature review .

Posted 11/10/2026internshipParis • FranceEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in computer vision and machine learning, with strong capabilities in Python and PyTorch for processing video streams and developing models. Proficient in conducting rigorous experiments and synthesizing research findings in technical English.

Highest-signal resume keywords

Python ProgrammingPyTorch FrameworkObject DetectionMulti-Object TrackingGenerative Models

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningApplied MathematicsVideo Stream ProcessingEvaluation ProtocolsData AnnotationPixel-Level BaselinesTemporal Consistency MeasurementSelective AnonymisationFailure Mode CharacterizationResearch Literature Review

Soft Skills

Rigorous ExperimentationIndependent Research Progression

Certifications & Qualifications

Mandatory Internship Agreement

Industry Keywords

Computer VisionPersonal Data ProtectionTracking-Based AnonymisationEvent AppearancesVizzia Data

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Conduct a literature review
Build test sets from public benchmarks and long Vizzia sequences, including annotating part of the data
Define evaluation protocols and metrics before the main experiments
Subject A: implement pixel-level baselines and low frame rate tracking; design an object-centric scene memory; model object states over time; characterize failure modes; evaluate event appearances and disappearances
Subject B: build detect-then-blur baselines; measure missed detections and tracking-based anonymisation; compare generative replacement methods; ensure temporal consistency; develop selective anonymisation for clips delivered to local authorities; measure privacy protection against utility
Deliver a model or pipeline evaluated on public and Vizzia data, a documented benchmark, clean code, integration recommendations and a master's thesis
Potentially continue as a CIFRE PhD

Requirements

What you’ll need

Final-year student in an M2 or engineering school, specialised in computer vision, machine learning or applied mathematics
Fluent in Python and PyTorch
Comfortable processing video streams
Subject A: knowledge of object detection, multi-object tracking or visual representation learning
Subject B: knowledge of generative models (GAN, diffusion, inpainting), detection, tracking or re-identification, and an interest in personal data protection
Technical English good enough to read and synthesize research papers
Rigorous with experiments and able to move a research question forward on your own
Mandatory internship agreement from your school

Benefits

Comp & perks

Hybrid work
Mandatory internship agreement from your school
1 day off per month
MacBook or PC
60% coverage of meal vouchers worth €9 per day worked
50% Navigo pass reimbursement
Annual offsite with the whole team
Plenty of company events