Job details
Overview:
University of Doha for Science and Technology (UDST) is the first national applied University in the State of Qatar, offering applied Bachelor and Master's degrees in addition to certificates and diplomas in various fields. UDST has over 50 programs in the fields of Engineering Technology and Industrial Trades, Business Management, Computing and Information Technology, Health Sciences, Continuing and Professional Education and more. With more than 600 staff and over 7,000 students, UDST is the destination for top-notch applied and experiential learning. The University is recognized for its student-centered learning and state-of-the-art facilities. Our faculty are committed to delivering pedagogically-sound learning experiences with the incorporation of innovative technological interventions, to further enhance students' skills and help develop talented graduates that can effectively contribute to a knowledge-based economy and make Qatar's National Vision 2030 a reality.
Applied Research Position:
The Applied Research, Innovation and Economic Development Directorate invites applications for the position of Research Assistant/Associate to work on a project on Intelligent Transportation Systems (ITS) funded by QRDI.
Application Procedure:
The application should be in English.
The application should be sent electronically and be attached as PDF-files, as below. Maximum size for each file is 10 MB.
CV: (Please name the document as: CV, Surname, Ref. number)
including:
A complete list of publications
Previous research experiences
Two references who can be approached to write letters of reference/recommendation
Cover letter: (Please name the document as: Personal letter, Family name, Ref. number)
1-3 pages where you:
Introduce yourself
Describe your previous research fields and main research results
Relate your qualifications, experience, and skills with the job requirements
Describe your future goals and future research focus
Responsibilities:
Your Commitment:
The successful candidate will help in implementing the project which is on Improving Traffic Sustainability, Resilience, Robustness, and Safety on Roads Through Connected Vehicles. The project is built upon an AI-based Joint Transportation and Communications V2X Framework. In particular, the potential candidate will support the research toward the development of intelligent technologies to deal with communication link failures and their impact on ITS and seek solutions to improve different aspects of traffic despite such deficiencies. The successful candidate will also be responsible for performing required simulations, manuscript writing, and preparing project reports. The successful candidates will interact with researchers and stakeholders (local and international collaborators and institutions) with respect to the related projects.
Qualifications:
Qualifications:
The candidates for the Research Assistant/Associate position must respectively have MSc/PhD in Electrical Engineering (communication engineering subfield). The potential candidates should have a demonstrated record of scholarship and a track record of excellence in research on ITS and path-planning algorithms. Being familiar with AI-based optimization is a plus. Familiarity with software packages such as SUMO, NS2, and OPNET is a plus. Fluency in written and spoken English is required. We are looking for both short-term (3-6 months) and long-term (1 year or more) appointments.
Preferable research experiences:
Experience in path-planning algorithms (cars, drones, etc)
A good publication record of the position-related papers published in peer-reviewed journals (This will be normalized to the years active in research)
Ability to work effectively as a part of a multi-disciplinary research team, and to carry out independent individual research to meet project goals
Advanced written and oral communication skills
Outstanding hands-on skills, strong computational and problem-solving skills, and a high level of analytical ability
Willingness to cooperate and support other researchers in the research lab
#J-18808-Ljbffr Science, Research and Teaching
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