Connectionists: PhD and post-doc position on Asynchronous Computer Vision from Event Cameras

[Ioan Marius Bilasco]

Dear candidates,

The FOX <https://www.cristal.univ-lille.fr/FOX/> team ofthe CRIStAL 
<https://www.cristal.univ-lille.fr/en/?force_lang=true> laboratory (UMR 
CNRS), Lille,France,and the PR 
<https://www.mis.u-picardie.fr/index.php/equipe/perception-robotique> 
team ofthe MIS <https://www.mis.u-picardie.fr/> Laboratory, 
Amiens,France,are looking to recruit :
* a post-doc starting as soon as possibleand;
* a joint PhD student starting in October 2025
in the field of*async**h**ronous computer vision from event camera**s**.*
*Abstract*: Video analysis is one of the fundamental tasks in computer 
vision. The dominant approach is based on deep neural networks applied 
to RGB images. These models have disadvantages such as: a) the need of 
large quantities of annotated data, which requires significant human 
work; b) the significant computational and therefore energy cost of 
these approaches; and c) redundancy in terms of visual information 
between two successive images. Spiking neural networks can offer a 
solution to these problems, through the use of unsupervised learning 
rules inspired by biological learning and the possibility of 
implementing them on ultra-low energy hardware components. . Event 
cameras that only communicate changes in light intensity are positioned 
as an alternative for capturing a scene when efficient processing on 
hardware with low computing capabilities is required. The objective of 
this thesis is to offer a joint response by proposing weakly supervised 
learning methods based on spiking learning mechanisms which will 
directly exploit the flow of impulses generated by an event camera. We 
are targeting applications around autonomous driving, such as the 
detection of moving vehicles or the recognition of information conveyed 
by large displays along the road infrastructure.
The main objective is to develop new models of spiking neural networks 
(SNN) capable of directly processing visual information in the form of 
spike trains. The proposed models must be validated experimentally on 
dynamic vision databases, following standard protocols and best practices.
*Candidates for the PhD *must hold a Master degree (or an equivalent 
degree) in Computer Science, Statistics, Applied Mathematics or a 
related field.

*Candidates for the post**-**doc *must hold a PhD degree inComputer 
Science, Robotics, Statistics, Applied Mathematics or a related field.

Experience in one or more of the following is a plus:
  • image processing, computer vision;
  • machine learning;
  • bio-inspired computing;
  • research methodology (literature review, experimentation…).
  Candidates should have the following skills:
  • good proficiency in English, both spoken and written;
  • scientific writing;
  • programming (experience in C++ is a plus, but not mandatory).
The *PhD candidate* will be funded for 3 years (/grant application 
pending/).He/She is expected to defend his/her thesis and graduate by 
the end of the contract. The monthly gross salary is around 2000€, 
including benefits (health insurance, retirement fund, and paid vacations).

The *post**-**doc *will be hiredfor 18 months starting from March 
2025(this is a fully-funded position). The monthly gross salary is 
around 2500-3000€, including benefits (health insurance, retirement 
fund, and paid vacations).
For application, please send the following itemsin a single PDF file to 
Pr. Marius Bilasco (marius.bilasco at univ-lille.fr) andtoDr. Fabio Morbidi 
(fabio.morbidi at gmail.com) with subject [EventSpike]:
  * A cover letter.
  * A curriculum vitae, including a list of publications, if any.
  * Transcripts of grades of Master's degree or transcripts/reports 
fromthe PhDdefense.
  * The contact information of two references (and anysupportletters,if 
available).
We look forward to receiving your application as soon as possible but no 
later than *12**April **2025.*

*Context of the projet**:*
The FOX research group is part of the CRIStAL laboratory (University of 
Lille, CNRS), located in Lille, France. We focus on video analysis for 
human behavior understanding. Specifically, we develop spatio-temporal 
models of motions for tasks such as abnormal event detection, emotion 
recognition, and face alignment. We are also involved in IRCICA (CNRS), 
a research institute promoting multidisciplanary research. At IRCICA, we 
collaborate with computer scientists and experts in electronics 
engineering to create new models of neural networks that can be 
implemented on low-power hardware architectures. Recently, we designed 
state-of-the-art models for image recognition with single and 
multi-layer unsupervised spiking neural networks. We were among the 
first to succesfully apply unsupervised SNNs on modern datasets of 
computer vision. We also developed our own SNN simulator to support 
experiments with SNN on computer vision problems.Our work is published 
in major journals (Pattern Recognition, IEEE Trans. on Affective 
Computing) and conferences (NeurIPS, WACV, IJCNN) in the field.

The PR (Robotic Perception) team is specializedin mobile robotics 
(perception), 3D reconstruction and unconventional vision. The PR team 
is leadingthe e-Cathedral program and is currently involved in 
threeprojects dealing witheventcameras: the ANR CERBERE project 
(2022-2025), the ANR DEVIN project (2024-2028) and theinternational 
(France-Austria) ANR-FWF EVELOC project (2024-2028). The PR team wishes 
to further strengthen this area of research and improve its expertise in 
AI bycollaboratingwith the CRIStAL laboratory.

The positions are located in Lille, France. With over 110 000 students, 
the metropolitan area of Lille is one France's top education student 
cities. The European Doctoral College Lille Nord-Pas de Calais is 
headquartered in Lille Metropole and includes 3,000 PhD Doctorate 
students supported by university research laboratories. Lille has a 
convenient location in the European high-speed rail network. It lies on 
the Eurostar line to London (1:20 hour journey). The French TGV network 
also puts it only 1 hour from Paris, 35 mn from Brussels, and a short 
trips to other major centres in France such as Paris, Marseille and Lyon.

==
Ioan Marius BILASCO
Professeur des Universités en Informatique
Univ. Lille
CRIStAL CNRS - UMR 9189
Cité Scientifique
59650 Villeneuve d'Ascq Cedex - France
https://pro.univ-lille.fr/marius-bilasco/
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