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Postdoctoral position in autonomous drone navigation

Opening for: Postdoc

Status details

Status:Closed
Announced:16 Mar 2020
Closing date:21 Aug 2020
Duration:2 years
Autonomous on-board drone navigation (i.e., without human intervention) in inaccessible environments is a fundamental challenge. The goal in this project is to develop novel machine learning algorithms for autonomous drone navigation in outdoor environments including localization and synchronization for BVLOS (beyond visual line of sight) scenarios and/or GPS-denied environments, by utilizing RF signals from fixed ground stations and/or in collaboration with other drones. This includes robust holistic 3D perception through sensor fusion of on-board sensors, for e.g., lidar, radar, camera, and inertial measurement units (IMUs), algorithms for detect and avoid using advanced machine learning for object detection, object classification, and ego-motion estimation. The proposed resource-constrained algorithms will be energy-efficient and robust for in-drone perception, cognition, and control.

About the project The Postdoctoral (and PhD) positions are a part of the recently funded ECSEL-H2020 project named ADACORSA (Airborne data collection on resilient system architectures), with over 50 partners across Europe. Circuits and Systems (CAS) group in the Faculty of EEMCS at TUD is one of the WP leaders (among 8) in this consortium, and will develop ground-breaking algorithms to realize efficient, robust, and data-fusion based cost-effective perception and control for autonomous drones. The overarching goal of this project is to provide technologies to render drones as a safe and efficient component of the mobility mix, with reliable capabilities in extended BVLOS operations.

Opening also at academictransfer.com

Requirements

We are looking for enthusiastic candidates that meet the following requirements.
  • A PhD degree in a relevant area e.g., electrical engineering, computer science or aerospace
  • The successful Postdoctoral candidate has a strong background in mathematical modelling and algorithm development in statistical signal processing (and/or machine learning) with applications to navigation, localization, control systems, sensor fusion for e.g., camera, lidar, radar.
  • Strong experience in programming e.g., Python, MATLAB, R
  • Candidate is pro-active, and combine creativity with a sound academic attitude with good analytical skills
  • Excellent communication skills in English, both in writing and speaking
  • Good team-player, and able to work in a collaborative environment with the other PhD, group members, and consortium members in the project.
  • Strong experience in programming e.g., Python, MATLAB, R
When you apply for any of these positions, please annex the following documents in SINGLE PDF with a filename “LastName_GraduationYear.pdf”, where “GradutationYear” is the graduation year of your PhD
  • Curriculum vitae
  • Motivation letter (max. 1 page)
  • A detailed list of university courses with grades, and list publications (if any)
  • Full contact information of two references who are acquainted with the applicant's previous academic and/or research/professional activity.

Contact

dr. Raj Thilak Rajan

Assistant Professor

Circuits and Systems Group

Department of Microelectronics

Related project

Airborne data collection on resilient system architectures

Develop algorithms to realize efficient, robust, cost-effective perception and control for autonomous navigation of drones