An Airborne Multi-Static Radar (AMR) system comprises multiple transmitters and receivers positioned on various distinct airborne platforms. To fully harness the advantages of an AMR system, numerous signal processing hurdles must be addressed. As a doctoral candidate within the Department of Electrical Engineering, you will play a crucial role in tackling these stimulating and dynamic advancements.
PhD Project Description
Your primary obligation is to conduct research aligned with the project's objectives, publish and deliver scientific articles, and engage in academic discussions. Within the scope of your doctoral pursuits, you will undergo additional educational training through courses pertinent to your research, the research project itself, signal processing in a comprehensive context, and your future professional endeavors. Moreover, you will be required to actively contribute to teaching efforts in related subject areas.
Qualification
A solid educational foundation in Engineering Mathematics, Engineering Physics, or Electrical Engineering is essential, with a strong academic record in the fundamental courses of these disciplines. Having expertise in signal processing, radar systems, estimation/detection, and statistical signal processing would be advantageous. The minimum qualification sought is a master's degree, equivalent to a minimum of 250 higher education credits, in fields such as engineering physics, electrical engineering, mathematics, or related areas.
The ideal candidate for this role should demonstrate a strong thirst for acquiring new knowledge, a keen interest in conducting theoretical yet highly relevant research, and a willingness to contribute to a diverse international academic environment. Proficiency in both written and spoken English is mandatory.
How to Apply
The application is only to be submitted online by using the"Apply online" button below. Please be notified that application deadline is 31 October 2023. For further information related to the PhD scholarships, please visit the following Scholarship Link.
For questions, please contact:
Prof. Tomas McKelvey, division of Signal processing and Biomedical Engineering
tomas.mckelvey@chalmers.se, 031-7728061
