Phd optimizing deep learning models for low power mcus.

Job description

You will be part of a team investigating a system that monitors a given area in a privacy-preserving manner (without using cameras).

Monitoring is central to the efficient and safe operation of smart homes, buildings, and cities. For example, monitoring systems may need to report an intruder breaking into a house or request help for an elderly person living alone who has fallen.

The challenge is that most monitoring systems rely on cameras, and citizens are becoming increasingly concerned about their abuse by governments or corporations. Together with a leading Dutch company, Signify, we aim to investigate monitoring platforms that cannot provide personalized information, even if they are hacked.

To achieve our goal, we are investigating platforms at the intersection of deep learning and embedded systems. We want to develop a system that is accurate but works with limited computational and energy resources.

Our work will have two main components: the sensors gathering data in a private manner (such as mmWave radars) and the deep learning models processing the data. This PhD position will focus on the deep learning part. Your PhD research will tackle two fundamental challenges: limited data and limited energy:

• Privacy-aware sensors provide significantly less data than cameras, but the deep learning models will still need to identify the events of interest accurately.
• The platforms will use batteries and are expected to have a long lifetime. Hence, the deep learning models must be optimized not only for accuracy but also for energy consumption.

The PhD research will take a holistic approach, including the design of the embedded system, the optimization of the machine learning models, and the connection with edge and cloud services.

This position is a joint collaboration with Signify, a leading Dutch company formerly known as Philips Lighting. During the PhD program, the candidate will spend approximately 80% of their time in Delft and the remaining time in Eindhoven, where Signify is located.

Job requirements

The applicant should have a Master Degree in Computer Science (preferable), Electrical/Electronic Engineering, or a closely related field. A solid knowledge of deep learning is required. Experience on Embedded Ai is desired but not required.

The position demands a strong background to build new prototypes and perform experimental work. The successful applicant should have good English language proficiency and a team player personality.

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.

Coming to Delft ServiceDual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Additional information

Application procedure

30 March 2025

• CV
• Motivational letter
• Bachelor's and Master's transcripts (list of courses and grades).

The curriculum vitae should include:

• The names and contact information of at least two references, but no more than three.
• List of publications (if any).
• The rank of the attended universities. Provide a link supporting the provided rank.
• The rank in the graduating class (if available). For example: Xth out of Y students, or top x%. Provide a document validating the class rank (if available).

The planned starting date of the position is negotiable but no later than September 2025

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:

• 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.