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Job ID: 128959

Ph.D. Scholarship on Docitive machine learning strategy for ultra-reliable and low-latency comm.
Ecole de Technologie Superieure


Date Posted Sep. 11, 2019
Title Ph.D. Scholarship on Docitive machine learning strategy for ultra-reliable and low-latency comm.
University Ecole de Technologie Superieure
Montreal, QC, Canada
Department Département de électrique
Application Deadline Open until filled
Position Start Date Available immediately
 
 
  • Graduate Student
  • Electrical and/or Electronics
    Engineering - Other
 
 

Ph.D. Scholarship in Electrical Engineering
With research focus: A Docitive Machine Learning Strategy for Ultra-Reliable and Low-Latency Communications


Scholarship Description


Thriving in today's exponentially growing economy requires the fusion of cutting-edge innovations to produce a ground-breaking product that excels in every performance measure. Artificial intelligence (AI), enabled by machine learning (ML), has revolutionized technology and opened venues in many fields. This scholarship is a part of an ambitious project that introduces ML to tactical wireless networks (TWN), an advanced form of wireless communication which is designed to be robust and reliable in constantly changing tactical situations, and varying environments. TWN provides secure links for voice, data, and video among mobile users to facilitate command and control within, and in support of, tactical missions. Additionally, the installation of TWN must be established autonomously and in a concise time to meet the frequent relocation demands of the users. The application of TWC varies from civil applications such as hazard release and rescue missions to military applications.
This scholarship is a part of an industrial chair on Intelligent Tactical Wireless Networks for Challenging Environments,' sponsored by Ultra Electronics TCS the leading company in robust communication systems and held by Prof. Georges. Kaddoum, a well-established researcher in the area of wireless communications and its related fields. The Ph.D. student will be working on a Docitive Machine Learning Strategy for Ultra-Reliable and Low-Latency Communications (uRLLC). The student will address the reliability and latency of the connection in the context of mission-critical communications. He/she will develop and optimize a machine learning algorithm to automatically update the network parameters to ensure uRLLC under several distortion sources such as interference, deep fading, or collusion. The student will work in a group of researchers, professional engineers, and graduate students in a collaborative fashion to achieve long-term objectives and short-term milestones. The scholarship is granted for three years with research duties exclusively, extendable for one year for justified exceptional achievements.

Environment Description


The Ph.D. program will be hosted by École de Technologie Supérieure (ÉTS), a trusted name in the Canadian industry with a rapidly growing reputation in research. With its state-of-the-art facilities, the Ph.D. program at ÉTS allows students to advance their intellectual rigor, their scientific curiosity and the creativity they need to resolve complex issues both in the industry and in challenging scientific research.
The award Ph.D. student will be affiliated with the Communication and Microelectronic Integration Laboratory (LaCIME). It brings together internationally renowned researchers supported by a team of students, trainees and professionals who use state-of-the-art tools to conduct innovative and highly applied research. This facility provides a world-class wireless communication R&D environment to develop hardware/software of future-generation physical-layer solutions for high-performance wireless communication networks. The synergy between its members as well as the diversity and complementarity of their expertise make LaCIME a unique laboratory and a privileged partner of industrialists. Additionally, ÉTS students enjoy the benefits of many research resources and facilities such as CenTech, LabVI, ÉTS library. Due to its strategic location at the heart of Montreal, ÉTS also has strong ties with its neighbor world-class universities such as Concordia, McGill, as well as industry head-quartiers which enables affiliated trainees to involve in industry-funded projects.

Qualifications and Requirements


All applicants should hold a master's degree with an excellent/very-good GPA in Electrical Engineering or Computer Science, or a related discipline. Applicants should demonstrate excellent English skills in writing, communication and presentation. He/she must be strongly motivated for doctoral studies, must demonstrate the ability to work independently and to perform critical analysis.
Candidates are asked to possess fundamental knowledge and skills in two or more of the following areas:
•     Excellent academic record, particularly in the analytical and theoretical subjects.
•     Strong analytical skills in wireless communication theory, stochastic processes, mathematical foundations of modern machine learning systems and techniques.
•     Background in wireless technology (PHY/MAC/Network).
•     Strong coding skills using MATLAB, Python, and C++ is a strong addition.
•     Prior experience/education in both theory and practice of machine learning is a plus.
•     Hands-on experience using one of the following deep learning libraries: TensorFlow, PyTorch, Caffe2, Theano, Keras, and/or Chainer
•     Good publication record on the subject is a plus.
•     Pass the admission requirements for ÉTS: https://www.etsmtl.ca/en/Studies/Admission

Role and Responsibilities


•     Complete the required credit hours stated in the ÉTS guidelines.
•     Perform research and participate in research activities to advance science and technology of intelligent wireless networks, hence publishing scientific articles in conference and journals periodically.
•     Work towards the long-term goals of the assigned project, while identifying intermediate milestones.

Scholarship Benefits


This scholarship will offer you competitive financial compensation for the delightful life standard at the beautiful city of Montréal. Additional to your academic progress, you will be enjoying the professional environment offered by ÉTS along with its state-of-the-art facilities and labs. This scholarship will encourage and support you financially to participate in international scientific conferences. You may also be eligible for excellence awards and other grants from Quebec and Canadian granting agencies during your study.
Furthermore, this scholarship will increase your chance to work in Quebec either in the academic or industrial track at internationally recognized universities and leading companies, especially Ultra Electronics-TCS. The Strategy for Research and Innovation of Quebec aims to make it one of the most innovative and creative societies in the world by 2030. Several financial initiatives have been put in place to support researchers, boost the innovations, and maximize the transfer and benefits of the technological revolution. Moreover, Montreal is a nerve center for several leading-edge high-tech fields in applied engineering, information and communications technologies, and artificial intelligence.

How to Apply


Interested applicants must fill this form and attach the following documents, in a single PDF file with the shown order:
•     Detailed CV
•     M.Sc. & B.Sc. transcripts
•     List of all publications
•     Softcopy of all publications (if available)
•     Statement of purpose for the envisioned research in context of this scholarship.
•     Two letters of recommendations
•     Contact info of two references
For additional information, please feel free to contact the same email.
For more information about Ultra Electronics TCS and graduate program at ÉTS, please visit https://www.ultra-tcs.com/ and: https://www.etsmtl.ca/en/Studies/Admission respectively.


 
Please reference AcademicKeys.com in your cover letter when
applying for or inquiring about this job announcement.
 
 

Contact Information

 
  • Mohammad T. Alkhodary
    Département De
    Ecole De Technologie Superieure
    Montreal, QC
    Canada
  •  
  • ets.positions@gmail.com

 

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