PhD in machine learning for autonomous drone navigation

PhD in machine learning for autonomous drone navigation

Published Deadline Location
30 Mar 24 Apr Delft

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Job description

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 PhD (and Postdoctoral) 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.


Delft University of Technology (TU Delft)


We are looking for enthusiastic candidates that meet the following requirements.
• MSc 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
• Pro-active, and combine creativity with a sound academic attitude with good analytical skills
• Excellent communication skills in English is desired, both in writing and speaking
• Good team-player, and able to work in a collaborative environment with the other Postdoc, 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 MS
• 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.

Conditions of employment

Fixed-term contract: 4 years.

TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit for more information.


Technische Universiteit Delft

Delft University of Technology (TU Delft) is ranked globally among the top 20 in engineering and technology, both in the Times Higher Education World University Rankings and the QS world rankings. TU Delft is a multifaceted institution offering education and carrying out research in the technical sciences at an internationally recognised level. Education, research and design are strongly oriented towards applicability. TU Delft develops technologies for future generations, focusing on sustainability, safety and economic vitality. At TU Delft you will work in an environment where technical sciences and society converge. TU Delft comprises eight faculties, unique laboratories, research institutes and schools.


Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of EEMCS brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers strengthen each other. We are mapping out disease processes using single-cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this challenging environment.

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.


  • PhD
  • Engineering
  • 38—40 hours per week
  • €2325—€2972 per month
  • University graduate
  • EWI2020-32


Delft University of Technology (TU Delft)

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