PhD Position in Co-Design for Neuromorphic Control
Derive a novel theoretical framework based on control theory to unlock the efficiency of neuromorphic compute in multi-timescale processing.
Job description
Neuromorphic computing promises new energy efficiency records by taking inspiration from biology. However, while the leaky integrate-and-fire (LIF) neuron is the current de-facto neuron model in neuromorphic hardware, it embeds only one single time constant limited to a few tens of milliseconds. This simple unit is limiting the learning capabilities of recurrent neural network models in tasks characterized by multi-timescale and long-range temporal dependencies.
To implement multi-scale adaptation, in this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent developments of adaptive control for event-based systems.
You will drive a novel theoretical framework to learn with bio-inspired multi-scale recurrent neural networks, and design custom neuromorphic hardware that will demonstrate an efficiency advantage on complex temporal scenes based on multi-scale computing units.
At TU Delft, you will be joining the CogSys team (https://cogsys.tudelft.nl/), supervised by Dr. Charlotte Frenkel.
This project will be co-supervised by Prof. Rodolphe Sepulchre at KU Leuven.
On top of participating to the yearly annual retreats organized by the doctoral network participants, you will complete several internships:
- one short internship at Innatera to ramp up on edge platforms,
- one or several long internships at KU Leuven with Prof. Rodolphe Sepulchre.
Job requirements
We are looking for a highly motivated Ph.D. candidate. The background is preferably in electrical engineering, computer architecture, control, computational neuroscience, or similar fields. Unconventional backgrounds supported by a strong motivation are also welcome to apply.
You are genuinely curious about the brain and enjoy learning beyond your comfort zone. In the absence of previous background in hardware, machine learning, and/or neuroscience, you must have a keen interest to expand your expertise in these areas. While you are able to take initiative, you are also a team player in order to make the best of interdisciplinary collaborations in a research team and in the broader MSCA network.
Important eligibility conditions include:
- The applicant must hold an MSc degree by the time of the start of the position. As per the EU MSCA mobility rule, applicants cannot have resided or carried out their main activity (work, studies, etc.) in the Netherlands for more than 12 months in the 3 years immediately before the recruitement date.
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 of 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 Promovendus gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
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.
Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.
Additional information
If you would like more information about this vacancy or the selection procedure, please contact Dr. Charlotte Frenkel, via c.frenkel@tudelft.nl. and cc dr. Martin Lefebvre@tudelft.nl. Please include "MSCA Application" in the file.
The preferred starting date is in early 2026 (preferred) to mid 2026 (at the latest).
Application procedure
Are you interested in this vacancy? Please apply no later than 30 Nov 2025 via the application button and upload the following documents:
- a cover letter stating your background, motivation, and fit for the position (max 1 page);
- a detailed curriculum vitae (incl. a list of publications, if any);
- a list two to three references, incl. the MSc thesis supervisor, who are ready to submit a support letter upon request;
- transcripts for your BSc and (ongoing) MSc;
- a summary (max. 2 pages) of your MSc thesis.
You can address your application to Dr. Charlotte Frenkel.
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.
- As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
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