Internship | Algorithm unrolling with deep learning for radar


Den Haag

Education type


Internship and graduation project

Hours a week

Fulltime – 40


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What will be your role?

Future radars will make use of advanced algorithms, such as sparse reconstruction methods, to effectively recover information from the received signals. These algorithms typically involve the use of iterative schemes including inversion of potentially large matrices that do not always have an analytical form or an efficient representation. This limits the applicability of these advanced techniques in areas where fast real–time processing of large scale data is required, such as radar surveillance. At radartechnology we are investigated ways to circumvent this problem by using deep learning.

During the last years, there has been a growing interest in the radar community to explore the possibility of using deep learning for sparse reconstruction. The idea is to replace the on–line costly reconstruction process characterizing classical methods with an off–line training of a network that emulates the iterative algorithm with a fixed number of computations. This technique is called algorithm unrolling, and it combines the interpretability of the original algorithm that is unrolled with the high performance of data-driven approaches.

In this project, you will design a neural network that implements algorithm unrolling and test it on synthetic and experimental radar signals. You will conduct this project in collaboration with Prof. Geert Leus from Dept. of Microelectronics at Delft University of Technology.

You will perform this assignment in the Department of Radar Technology. We are a passionate and creative group of professionals (60 people) dedicated to the specification, development and evaluation of innovative, high-performance MMICs, miniaturised and integrated RF subsystems, antennas and front-ends. The department is at the heart of novel, game-changing radar system and signal processing concepts for the military, space and civil domains.

How do you want to contribute to tomorrow's world? How big can your impact be? Come and work at TNO and envision it.

What we expect from you

You are in the final stages of your degree in artificial intelligence, computer science, physics, mathematics, electrical engineering or a similar degree and have some track record in the field of signal processing and deep learning: this should be apparent in your application. You have experience in programming in Matlab and/or Python and are quick in understanding new software, and algorithms. You are pragmatic and focused on making things work. Next to technical expertise we value communication skills and a results-driven attitude.

What you’ll get in return

You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Naturally, we provide suitable work placement compensation.

TNO as an employer

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world. Read more about TNO as an employer.

The selection process

After the first CV selection, the application process will be conducted by the concerning department. TNO will provide a suitable internship agreement. If you have any questions about this vacancy, you can contact the contact person mentioned below.

Due to Covid-19 and the consequent uncertainties and restrictions, students who are not residing in the Netherlands may currently not be able to start an internship or graduation project at TNO.

Has this job opening sparked your interest?

Then we’d like to hear from you! Please contact us for more information about the job or the selection process. To apply, please upload your CV and covering letter using the ‘apply now’ button.

Contact: Lilian Martín Montón, de
Phone number: +31 (0)88 86 60708

Note that applications via email and third party applications are not taken into consideration.


Apply now



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