PhD Position Distributed & Adaptive Radar for Human wellbeing Monitoring

We seek a motivated PhD student to work on a 4-year NWO funded project called DARE (Distributed and Adaptive Radar for Enhanced Sensing and Classification).

The goal of this project is to work towards transitioning radar from a conventional stand-alone sensor to an intelligent and spatially distributed network of cooperative nodes. The spatially distributed aspect will provide information from many partial viewpoints to reconstruct more detailed 3D signatures of the observed scenarios. The intelligent aspect will enable the radar to adapt its parameters and processing to the changes in objects’ behavior and environment, like in a sort of “chess game”. Hence, the intended scientific breakthrough is to formulate, implement, and validate the ‘distributed radar brain’ needed to establish and support this new sensing approach, combining spatially-distributed with adaptive capabilities in radar classification.

Specifically, in this project we work on the problem of observing people and supporting their wellbeing. This is primarily looking at the context of monitoring drivers’ and passengers’ conditions in the cabin of future smart cars, as well as more in general the health condition of vulnerable individuals in an indoor environment (e.g., people with health conditions living alone who might suffer from accidents such as falls). This problem is scientifically challenging, as 1) indoor environments such as vehicle cabins present a lot of clutter and multipath masking the signature of the person or people to observe; and 2) the human body is a rather complicated object to observe with radar, as we want to observe reliably the very small movements associated to vital signs (e.g., heartbeat) and the larger movements such as a fall while walking. Distributed and adaptive radar techniques have the potential to improve our capabilities to monitor these situations, and we seek motivated students to take up this challenge.

During this PhD, you will work in the Microwave Sensing Signals and Systems (MS3) research group at the Department of Microelectronics of TU Delft. Being one of a few European radar groups in academia, this group has extensive research facilities and excellent track record on the full pipeline of microwave and radar sensing, from hardware development to signal processing and automatic object classification. Your direct working environment will include a large pool of PhD students of MS3 (please see our website: radar.tudelft.nl). You will also interact with the partner organizations that are part of the consortium of this project, all leading players in radar systems and related signal processing in the Dutch landscape and beyond. Moreover, in the same project another PhD vacancy is open, for the different application of monitoring drones that may pose safety concerns in public spaces.

Your main responsibilities will be to:

• Develop strategies to adapt the configuration of radars in a network and decide the best processing approaches as a function of the object behaviour and changes in the environment, which should be later translated into the codes and databases.
• Formulate mathematical models for key radar parameters, feature extraction, and identification/tracking for people observed by heterogeneous radar networks.
• Experimentally validate methods using numerical simulations and in-situ observations.
• Collaborate with another PhD student within the same project to exchange knowledge, perform joint experiments and make sure all project objectives are met.
• Participate in knowledge utilization activities and dissemination of research findings, also including project partners.

To be considered for this PhD position you should have:

• A Master's degree in electrical/electronic engineering, computer science, physics, mathematics or other related fields.
• Knowledge and interest in radar signal processing, preferably but not necessarily on classification techniques and distributed radar systems.
• Knowledge or at least some interest in machine learning, preferably techniques for management/adaptation of systems.
• Programming experience in MATLAB/Python or C/C++, preferably in relation to radar signal processing.
• A curiosity-driven mindset, the ability to learn new things and a passion for (doing) research. Evidences of innovative thinking and new knoweldge generation is an advantage.
• An open-minded personality for cooperation with colleagues and co-supervision of students.
• Willingness to help out with education related tasks (e.g., teaching assistance).
• Good English language and communication skills (written and oral) in order to closely cooperate with colleagues and students as well as write project documents.

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.

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 € 2770 per month in the first year to € 3539 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.

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!

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.