Postdoc Opportunity
SMAIL NIAR <smail.niar-uXtqY6lGdSDBlfn6S3fvzW/[email protected]> Thu, 26 Oct 2017 23:42:07 +0200
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--===============5625236625815799263== Content-Type: multipart/alternative; boundary="Apple-Mail=_1940D884-5301-46D7-8D21-C3936932D0DA" --Apple-Mail=_1940D884-5301-46D7-8D21-C3936932D0DA Content-Transfer-Encoding: quoted-printable Content-Type: text/plain; charset="utf-8" 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).=20 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=20 System-on-Chip Devices, G. Zhong, S.Niar, A.Prakash, T.Mitra, IEEE=20 Trans. Vehicular Technology 65(6), 2016. 2. An Accelerator for High Efficient Vision Processing, Z. Du,=20 S.Liu, R.Fasthuber, T. Chen, P. Ienne, L. Li, T. Luo, Q. Guo, X.=20 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=20 assistant application, H. Liu, S. Niar, IEEE/ACM DATE 2013. 4. Computer Vision for Autonomous Vehicles, J.Janai, F. G=C3=BCney, = 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). =20 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=20 Preferred starting date: 01/12/2017 but not later than 01/02/2018 Contact: Professor Sma=C3=AFl NIAR Smail.niar-uXtqY6lGdSDBlfn6S3fvzW/[email protected] = <mailto:Smail.niar-uXtqY6lGdSDBlfn6S3fvzW/[email protected]> <mailto:Smail.niar-uXtqY6lGdSDBlfn6S3fvzW/[email protected] = <mailto:Smail.niar-uXtqY6lGdSDBlfn6S3fvzW/[email protected]>> 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>> --Apple-Mail=_1940D884-5301-46D7-8D21-C3936932D0DA Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="utf-8" <html><body style=3D"word-wrap: break-word; -webkit-nbsp-mode: space; = -webkit-line-break: after-white-space;" class=3D""><div = class=3D"">Post-Doc: Neural Networks & Heterogeneous Multi-Core = Architectures for Autonomous Cars<br class=3D""><br = class=3D"">Post-Doctorate position Progresses in the design of CMOS = circuits have made the<br class=3D"">possibility to support very complex = Machine Learning (ML) algorithms using large<br class=3D"">data sets. = For this reason, AI techniques such as Convolution Neural Network<br = class=3D"">(CNN) and Deep Neural Network (DNN) have received recently = interests both in<br class=3D"">industry and academy to implement = complex applications.<br class=3D""><br class=3D"">In the domain of = embedded systems for automotive applications, CNN and DNN have<br = class=3D"">many potential applications, especially for Advanced Driving = Assistance Systems<br class=3D"">(ADAS) and autonomous driving. These = algorithms have shown high performances in<br class=3D"">scene = understanding and object/obstacle classification.<br class=3D""><br = class=3D"">This post-doc aims to contribute in the domain of embedded = system design for<br class=3D"">Real-time and automotive applications, = especially in autonomous driving. The objective here is<br class=3D"">to = develop new heterogeneous FPGA/GPU-based multiprocessor architectures = to<br class=3D"">support complex ML algorithms. The target heterogeneous = multi-core architectures<br class=3D"">must in one hand adapt the ML = algorithm and the supporting architecture to<br class=3D"">different = scenarios and on the other hand must use different CNN and DNN<br = class=3D"">configurations taking into account the different = characteristics of embedded<br class=3D"">sensors (Cameras, Lidars, = Radars). <br class=3D""><br class=3D"">The duties also include = collaboration with PhD students working on these topics<br class=3D"">and = helping to write high-impact papers and funding applications.<br = class=3D""><br class=3D"">The post-doc is within the framework of the = ELSAT 2020 project<br class=3D"">(<a = href=3D"http://www.frttm.fr/elsat2020" = class=3D"">http://www.frttm.fr/elsat2020</a>).<br class=3D""><br = class=3D"">Bibliography:<br class=3D""><br class=3D"">1. Design of = Multiple-Target Tracking System on Heterogeneous <br = class=3D""> System-on-Chip Devices, G. Zhong, S.Niar, = A.Prakash, T.Mitra, IEEE <br class=3D""> Trans. = Vehicular Technology 65(6), 2016.<br class=3D"">2. An Accelerator for = High Efficient Vision Processing, Z. Du, <br = class=3D""> S.Liu, R.Fasthuber, T. Chen, P. Ienne, L. = Li, T. Luo, Q. Guo, X. <br class=3D""> Feng, Y. = Chen, and O. Temam, IEEE Transactions on CAD of Integrated Circuits<br = class=3D""> and Systems, 02/2017<br class=3D"">3. Radar = signature in multiple target tracking system for driver <br = class=3D""> assistant application, H. Liu, S. Niar, = IEEE/ACM DATE 2013.<br class=3D"">4. Computer Vision for Autonomous = Vehicles, J.Janai, F. G=C3=BCney, A.Behl, A.<br = class=3D""> Geiger, Datasets and State-of-the-Art. = CoRR, 2017.<br class=3D""><br class=3D"">Required degree and skills:<br = class=3D""><br class=3D""> * Ph.D in computer = engineering/electrical engineering/automation.<br class=3D""> * = Experience in scientific journals / conference publication with = good English<br class=3D""> (writing and speaking).<br = class=3D""> </div><div class=3D""> Knowledge/experience = in one of the following matters would be an advantage:<br class=3D""><br = class=3D"">1 Machine learning and AI techniques,<br class=3D""><br = class=3D"">2 Signal and/or image processing,<br class=3D""><br = class=3D"">3 Embedded FPGA-GPU-CPU systems, hardware architectures.<br = class=3D""><br class=3D"">An application prepared in English or French = should contain:<br class=3D""><br class=3D"">1. CV with the = list of publications.<br class=3D""><br class=3D"">2. = Contact information for 2 reference persons.<br class=3D""><br = class=3D"">Salary: 2500 euros/month Deadline: 30/11/2017 Duration: 18 = months <br class=3D"">Preferred starting date: 01/12/2017 but not = later than 01/02/2018<br class=3D""><br class=3D"">Contact: Professor = Sma=C3=AFl NIAR <a href=3D"mailto:Smail.niar-uXtqY6lGdSDBlfn6S3fvzW/[email protected]" = class=3D"">Smail.niar-uXtqY6lGdSDBlfn6S3fvzW/[email protected]</a><br class=3D""><<a = href=3D"mailto:Smail.niar-uXtqY6lGdSDBlfn6S3fvzW/[email protected]" = class=3D"">mailto:Smail.niar-uXtqY6lGdSDBlfn6S3fvzW/[email protected]</a>> LAMIH/CNRS = - University of<br class=3D"">Valenciennes, France. <a = href=3D"http://www.univ-valenciennes.fr/LAMIH/membres/niar_smail" = class=3D"">www.univ-valenciennes.fr/LAMIH/membres/niar_smail</a><br = class=3D""><<a = href=3D"http://www.univ-valenciennes.fr/LAMIH/membres/niar_smail" = class=3D"">http://www.univ-valenciennes.fr/LAMIH/membres/niar_smail</a>>= ;<br class=3D""></div></body></html>= --Apple-Mail=_1940D884-5301-46D7-8D21-C3936932D0DA-- --===============5625236625815799263== Content-Type: text/plain; charset="utf-8"; name="ATT00001" MIME-Version: 1.0 Content-Transfer-Encoding: base64 Content-Disposition: inline; filename="ATT00001" Content-Description: ATT00001 X19fX19fX19fX19fX19fX19fX19fX19fX19fX19fX19fX19fX19fX19fX19fX18KQ29uY3VycmVu Y3kgbWFpbGluZyBsaXN0CkNvbmN1cnJlbmN5QGxpc3RzZXJ2ZXIudHVlLm5sCmh0dHA6Ly9saXN0 c2VydmVyLnR1ZS5ubC9tYWlsbWFuL2xpc3RpbmZvL2NvbmN1cnJlbmN5Cg== --===============5625236625815799263==--