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<p>Hi,<br>
</p>
<p>We are looking for a highy motivated Master’s level (M2) student
or final-year engineering student for an internship focused on
deepfakes. This internship will take place within the SAFE team of
the GREYC laboratory (UMR 6072), a digital sciences research
laboratory based in Caen, Normandy, France.</p>
<p><b>CONTEXT</b><br>
The emergence of deepfakes and face-swapping techniques has
profoundly transformed the landscape of visual cybersecurity.
Thanks to generative models such as GANs and diffusion models, it
is now possible to produce hyper-realistic videos in which one
person’s face is replaced by another’s, in a way that is almost
imperceptible to the human eye.<br>
<br>
To counter this threat, many automatic deepfake detection models
have been developed, leveraging deep vision architectures such as
Convolutional Neural Networks (CNNs), Vision Transformers (ViTs),
and spatio-temporal models. These systems aim to identify subtle
artifacts introduced by generation algorithms (lighting
inconsistencies, compression artifacts, local facial deformations,
etc.).<br>
<br>
However, these detectors remain vulnerable to a new class of
threats: adversarial attacks. Such attacks consist of adding a
quasi-imperceptible perturbation to an image in order to fool an
artificial intelligence model. Among them, Universal Adversarial
Perturbations (UAPs) represent an advanced form of attack, as a
single perturbation can mislead a model across a large number of
images, or even an entire video stream.<br>
<br>
<b>OBJECTIVES</b><br>
The main objective of this internship is to evaluate the
robustness of deepfake detection systems. To this end, the intern
will design and assess universal adversarial perturbations (UAPs)
capable of deceiving deepfake detectors while remaining visually
imperceptible.<br>
<br>
This 4- to 6-month internship, starting on April 1st, is intended
for Master’s students or final-year engineering students with
strong knowledge in deep learning and neural networks,
particularly GANs, experience in computer vision and image
processing, and solid programming skills (Python, TensorFlow, or
PyTorch).<br>
<br>
<b>SUPERVISORS</b><br>
- Christophe Charrier, Full Professor, University of Caen
Normandy – <a class="moz-txt-link-abbreviated" href="mailto:christophe.charrier@unicaen.fr">christophe.charrier@unicaen.fr</a><br>
- Emmanuel Giguet, CNRS Research Scientist –
<a class="moz-txt-link-abbreviated" href="mailto:emmanuel.giguet@unicaen.fr">emmanuel.giguet@unicaen.fr</a><br>
</p>
<p><b>APPLICATION</b><br>
To apply, please send an application package by email to the
supervisors, including a CV, a cover letter, academic transcripts
from the last two years, and any additional material that may
strengthen the application (e.g., letters of recommendation).</p>
<p><b>APPLICATION DEADLINE</b>: February 28, 2026<br>
<br>
Best regards,<br>
<br>
Christophe Charrier<br>
</p>
<pre class="moz-signature" cols="72">--
Full Professor in Computer Science, Université de Caen Normandie
Research | Teaching
GREYC Lab., UMR CNRS 6072. | IUT Grand Ouest Normandie
Campus 2, 6 bd. Mal Juin. | Multimedia and Internet Dept.
F-14032, Caen | 120, rue de l'exode
| F-50000, Saint-Lô
Tel: +33 2 31 53 81 85 | +33 2 33 77 55 10
URL : <a class="moz-txt-link-freetext" href="https://charrierc.users.greyc.fr/">https://charrierc.users.greyc.fr/</a></pre>
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