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  3. Postdoc Machine Learning for Autonomous Drone Navigation

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Postdoc Machine Learning for Autonomous Drone Navigation

Challenge. Change. Impact!

10 maanden geleden


Mekelweg, Delft, Zuid-Holland
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 - 40 uur


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.

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. The 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.

Circuits and Systems (CAS) group at EEMCS (TUD) covers the theory and applications of signal processing, including high-level digital system design. Signal processing theory includes array signal processing, estimation and detection, sampling theory, graph signal processing, convex optimization, distributed processing, machine learning and tensor analysis. Application areas include audio and acoustics, wireless communication, radio astronomy systems, distributed sensing from space, biomedical signal and image processing (MRI, ultrasound, ECG), and computational platforms for autonomous driving (e.g., radar sensor fusion). The main goal in our research program is to provide a sound mathematical framework for the analysis and synthesis of problems in the complete trajectory from system application, signal processing model, algorithm design, mapping to a digital hardware architecture or embedded system or VLSI circuit, and finally the design verification.


We are looking for enthusiastic candidates that meet the following requirements.

  • PhD degree in a relevant area e.g., electrical engineering, computer science or aerospace
  • 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 this position, 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.


Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (salary indication: €3.353 - €4.402 per month). The TU Delft offers a customisable compensation package, a discount on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation. An International Children's Centre offers childcare and there is an international primary school.

Additional information

For information about this vacancy, you can contact Dr. Raj Thilak Rajan, Assistant professor, email: r.t.rajan@tudelft.nl, tel: +31152787115.

For information about the selection procedure, please contact Ms. M.F.E. van der Heijden, HR-Adviser, email: vacancies-eemcs@tudelft.nl.