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.
Department 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.
Requirements 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.
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 Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (salary indication: €3255-€4274 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.
TU Delft (Delft University of Technology) 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. For generations, our engineers have proven to be entrepreneurial problem-solvers both in business and in a social context. TU Delft offers 16 Bachelor’s and 32 Master’s programmes to more than 23,000 students. Our scientific staff consists of 3,500 staff members and 2,800 PhD candidates. Together we imagine, invent and create solutions using technology to have a positive impact on a global scale.
Challenge. Change. Impact!
Faculty Electrical Engineering, Mathematics and Computer Science The Faculty of Electrical Engineering, Mathematics and Computer Science (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 reinforce 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 here 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 innovative environment.
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Additional information For information about this vacancy, you can contact Dr. Raj Thilak Rajan, Assistant professor, email: firstname.lastname@example.org, tel: +31152787115. For information about the selection procedure, please contact Ms.M.F.E.vanderHeijden, HR-Adviser, email: email@example.com.
Application procedure To apply, please e-mail a detailed CV with publication list, a motivation letter, a research statement and contact details of 2-3 references by June 30, 2020 to Drs. M.F.E. van der Heijden, firstname.lastname@example.org mentioning vacancy TUD00127.
A pre-employment screening can be part of the application procedure.