[ecoop-info] Postdoc Opportunity

[SMAIL NIAR]

Post-Doc: Neural Networks & Heterogeneous Multi-Core Architectures for Autonomous Cars

Post-Doctorate position Progresses in the design of CMOS circuits have made the
possibility to support very complex Machine Learning (ML) algorithms using large
data sets. For this reason, AI techniques such as Convolution Neural Network
(CNN) and Deep Neural Network (DNN) have received recently interests both in
industry and academy to implement complex applications.

In the domain of embedded systems for automotive applications, CNN and DNN have
many potential applications, especially for Advanced Driving Assistance Systems
(ADAS) and autonomous driving. These algorithms have shown high performances in
scene understanding and object/obstacle classification.

This post-doc aims to contribute in the domain of embedded system design for
Real-time and automotive applications, especially in autonomous driving. The objective here is
to develop new heterogeneous FPGA/GPU-based multiprocessor architectures to
support complex ML algorithms. The target heterogeneous multi-core architectures
must in one hand adapt the ML algorithm and the supporting architecture to
different scenarios and on the other hand must use different CNN and DNN
configurations taking into account the different characteristics of embedded
sensors (Cameras, Lidars, Radars). 

The duties also include collaboration with PhD students working on these topics
and helping to write high-impact papers and funding applications.

The post-doc is within the framework of the ELSAT 2020 project
(http://www.frttm.fr/elsat2020 <http://www.frttm.fr/elsat2020>).

Bibliography:

1. Design of Multiple-Target Tracking System on Heterogeneous 
   System-on-Chip Devices, G. Zhong, S.Niar, A.Prakash, T.Mitra, IEEE 
   Trans. Vehicular Technology 65(6), 2016.
2. An Accelerator for High Efficient Vision Processing, Z. Du, 
   S.Liu, R.Fasthuber, T. Chen, P. Ienne, L. Li, T. Luo, Q. Guo, X. 
   Feng, Y. Chen, and O. Temam, IEEE Transactions on CAD of Integrated Circuits
   and Systems, 02/2017
3. Radar signature in multiple target tracking system for driver 
   assistant application, H. Liu, S. Niar, IEEE/ACM DATE 2013.
4. Computer Vision for Autonomous Vehicles, J.Janai, F. Güney, A.Behl, A.
   Geiger, Datasets and State-of-the-Art. CoRR, 2017.

Required degree and skills:

 *   Ph.D in computer engineering/electrical engineering/automation.
 *   Experience in scientific journals / conference publication with good English
   (writing and speaking).
 
   Knowledge/experience in one of the following matters would be an advantage:

1 Machine learning and AI techniques,

2 Signal and/or image processing,

3 Embedded FPGA-GPU-CPU systems, hardware architectures.

An application prepared in English or French should contain:

1.   CV with the list of publications.

2.   Contact information for 2 reference persons.

Salary: 2500 euros/month Deadline: 30/11/2017 Duration: 18 months 
Preferred starting date: 01/12/2017 but not later than 01/02/2018

Contact: Professor Smaïl NIAR Smail.niar at univ-valenciennes.fr <mailto:Smail.niar at univ-valenciennes.fr>
<mailto:Smail.niar at univ-valenciennes.fr <mailto:Smail.niar at univ-valenciennes.fr>> LAMIH/CNRS - University of
Valenciennes, France. www.univ-valenciennes.fr/LAMIH/membres/niar_smail <http://www.univ-valenciennes.fr/LAMIH/membres/niar_smail>
<http://www.univ-valenciennes.fr/LAMIH/membres/niar_smail <http://www.univ-valenciennes.fr/LAMIH/membres/niar_smail>>