Postdoc machine learning for autonomous drone navigation
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.
The postdoctoral position (one year, with a possibility of extension) is a part of the ongoing ECSEL-H2020 project named ADACORSA (Airborne data collection on resilient system architectures), with over 50 partners across Europe. The Circuits and Systems (CAS) group 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. CAS is one of the Department Microelectronics (ME) groups within the Faculty of EEMCS at TUD. The Postdoctoral candidate will work closely with various partners, to develop robust algorithms for sensor fusion and drone navigation (control)
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 management skills and planning skills
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.
Challenge. Change. Impact!
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. 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.
For more information, please contact Raj Thilak Rajan.