Job description

This groundbreaking project comprises four PhD positions, led by experts in radar technology, machine learning, and automotive engineering.

Radar images are often disturbed by noise, clutter, and interference, which sometimes leads to a misinterpretation of those radar images. Better understanding of the impact of noise and interference on radar analysis will lead to more robust interpretation of radar images and more reliable radar-based Advanced Driving Assistance Systems (ADAS) applications.

In the proposed project we have the following objectives:

• To use real and synthetic radar image datasets to train cutting-edge machine learning models for radar image interpretation, potentially yielding more reliable interpretations that are more resistant to radar clutter, clutter and interference, for both static and dynamic scenarios, where one or more target(s) need to be detected or followed.
• Rigorously assess and benchmark various existing and new ML approaches (neural networks and others) for the interpretation of radar data in the presence of radar clutter, noise and interference, for the case of static and dynamic scenarios, where one or more targets must be detected or tracked.

This PhD opportunity offers a stimulating and challenging experience, encompassing both theoretical and experimental aspects. It explores two cutting-edge disciplines— radar engineering and machine learning—within the context of Advanced Driving Assistance Systems.

Job requirements
Must-haves:

• MSc in machine learning, electrical engineering, computer science, mathematics, or equivalent
• Strong analytical skills
• Proven record in programming skills
• Proficiency in English
• Good communication skills
• Ability to work in a multidisciplinary, highly dynamic environment

Nice-to-haves:

• Background in machine learning, radar technology, or automative engineering

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 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 as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

Conditions of employment
Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2901 per month in the first year to € 3707 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Additional information
If you would like more information about this vacancy or the selection procedure, please contact Justin Dauwels, via j.h.g.dauwels@tudelft.nl.

Application procedure
Are you interested in this vacancy? Please apply no later than 16 Feb 2025 via the application button and upload the following documents:

• CV
• Motivational letter
• Letters of recommendation
• Recent publications
• List of courses + grades

You can address your application to Justin Dauwels.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Please note:

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening can be part of the selection procedure.
• For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the National Knowledge Security Guidelines. We carry out this check on the basis of legitimate interest.
• Please do not contact us for unsolicited services.