PhD Position in Robust Signal Processing for Automotive Radars

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PhD Position in Robust Signal Processing for Automotive Radars

Delft University of Technology
Country of Position: 
Contact Name: 
Nitin Jonathan Myers
Subject Area: 
Applies to General Signal Processing
Autonomous Systems Initiative
Signal Processing for Communications and Networking
Start Date: 
October 27, 2022
Expiration Date: 
January 31, 2023
Position Description: 

The Delft Center for Systems and Control (DCSC) at TU Delft is offering one PhD vacancy under the newly funded ‘Signal Processing for Environment-Aware Radar’ (SPEAR) project. The project will be carried out in the research group of Dr. N. J. Myers, in collaboration with researchers at the faculty of 3mE and the faculty of EEMCS. The PhD candidate will work on industry-relevant scientific challenges in collaboration with industry experts from NXP.

Dr. Myers’s group at TU Delft develops and analyzes novel signal processing techniques for communications and sensing with wireless systems. We focus on both applied and theoretical aspects of challenging problems in connected automotive and radars.

PhD project description: In next generation automotive networks, radars will be deployed in almost every vehicle to ensure safe driving. In such dense radar deployments, signals from multiple radars interfere with each other and deteriorate the perception capability of the radars.  This PhD project will develop new signal processing techniques, to construct multi-dimensional digital radar waveforms and algorithms, that ensure interference-robust radar operation even in dense automotive networks. Our techniques are also expected to adapt to the sensing environment, by leveraging information from various sensors in an automotive. 

Are you interested in this vacancy? Please check the job requirements and apply here before 31 January 2023.

Candidates are also encouraged to look at another PhD vacancy, within the project SPEAR, in the group of Dr. Geethu Joseph, EEMCS: PhD Position in Radar Signal Processing For Next Generation Vehicular Networks.

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