Offre en lien avec l’Action/le Réseau : – — –/– — –

Laboratoire/Entreprise : LAMSADE
Durée : 3 years
Contact : alexandre.allauzen@dauphine.psl.eu
Date limite de publication : 2021-09-03

Contexte :
This is a 3-year PhD position, funded by Foxstream, a software company
(since 2004), specialized in real-time automated processing of video
content analysis. The PhD thesis is a collaboration with Dauphine
Université (the MILES team of the LAMSADE) with a join supervision
(Quentin Barthélemy from Foxstream and Alexandre Allauzen from MILES).
The PhD student will be located at Paris-Dauphine University in close
relationships with Foxstream.

Sujet :
For a couple of decades, Deep Learning (DL) added a huge boost to the
already rapidly developing field of computer vision. While for some
kind of data and tasks, DL is the most successful approach, this is
not the case for all applications. For instance, the analysis of video
streams generated by thermal cameras is still a research challenge
because of the long range perimeter, the depth of focus and the
associated geometrical issues, along with the frequent calibration
change. Therefore, the stability and robustness of DL models must be
better characterized and improved.

Very recently, Transformer architectures have achieved state of the
art performances in many domains: from natural language processing to
computer vision. In this thesis we will explore the use of Tranformers
for videos generated by thermal cameras and their properties.

From a theoritical and application perspectives, the goals are to
explore the stability of such architectures, the robustness against
adversarial examples, and what kind of invariances and symetries can
be captured.

Profil du candidat :
– Outstanding master’s degree (or an equivalent university degree) in
computer science or another related disciplines (as e.g. mathematics,
information sciences, computer engineering, etc.).
– Proficiency in machine learning, computer vision, or signal
processing.
– Fluency in spoken and written English is required.

Formation et compétences requises :
Application:
To apply, please email alexandre.allauzen [at] dauphine.psl.eu with:
– a curriculum vitae, with contact of 2 or more referees
– a cover letter
– a research outcome (e.g. master thesis and/or published papers) of
the candidate
– a transcript of grades

Adresse d’emploi :
Université Paris Dauphine