Delft University of Technology

Engineers usually want predictability. This project embraces chaos! – Excited about control theory? Then join us to build the math of chaotic sampling for greener and more secure control systems.
Job Description
Wireless communication can make control systems cheaper and easier to deploy, but bandwidth and energy limitations, as well as vulnerability to cyber-attacks, restrict its use in critical applications. Event-based control approaches can greatly reduce communication by transmitting information only when required, while potentially generating complex, chaotic sampling patterns. This project investigates how such patterns can be designed systematically to make communication timing difficult for an external observer to predict, while maintaining closed-loop stability and using network resources efficiently.
In this PhD project, you will develop mathematical theory and computational methods for the analysis and design of chaotic sampling mechanisms in networked control systems. You will study conditions under which event-based sampling exhibits chaotic behavior and how to design controller and sampler strategies that account for stability, communication rate, and measures of timing unpredictability such as entropy. You will also investigate the robustness of these mechanisms to disturbances and assess whether transmission patterns can be learned from external observations.
This position is part of a new lab at the Delft Center for Systems and Control, supervised by Gabriel de Albuquerque Gleizer. The research will allow you to gain deep insights across nonlinear dynamics, optimization, and theoretical computer science, and to combine those in new innovative ways. The position will offer you the opportunity to work on important problems with real-world impact and a strong publication potential. As the project progresses, you will also have the freedom to contribute to an experimental demonstration using a wireless lab-scale control system. Still, this position is theory-centric: expected outcomes include theoretical results, mathematical proofs, and computational algorithms, as well as open-source software and validation through simulations and analysis. Experimental demonstration is an option if it interests you.
Teaching activities are part of your PhD trajectory and may include, for example: supervising workgroups or lab sessions, assisting in courses, or mentoring BSc and MSc students. While teaching will not be your main responsibility, it offers valuable experience that supports your development and prepares you for future academic or professional roles. Teaching activities will not exceed 20% of your total appointment, averaged over the course of your PhD.
Essential
Job requirements
<ul>
<li>An MSc degree in systems &amp; control, electrical engineering, mechanical engineering, applied mathematics, physics, theoretical computer science, or a closely related field.</li>
<li>Strong enthusiasm for mathematics and abstraction, matched with the motivation to conduct theory-driven research, the ability to develop rigorous mathematical arguments, and a drive to improve these skills.</li>
<li>Curiosity about chaos, nonlinear dynamics, and unpredictability.</li>
<li>Solid foundations in linear algebra and differential equations.</li>
<li>Proficiency in scientific programming and an excellent command of English.</li>
</ul>
Advantages (but not required)
<ul>
<li>Background in systems and control. For example, familiarity with stability analysis, state-space methods, jump-flow systems, or continuous-time and discrete-time LTI systems theory is a plus.</li>
<li>Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning.</li>
<li>Prior knowledge on nonlinear dynamics, dynamical systems theory, networked control systems, event-based control, discrete-event systems, or theoretical computer science is not a requirement, but it is an advantage.</li>
</ul>
Advantages (but not required)
<ul>
<li>Background in systems and control. For example, familiarity with stability analysis, state-space methods, jump-flow systems, or continuous-time and discrete-time LTI systems theory is a plus.</li>
<li>Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning.</li>
<li>Prior knowledge on nonlinear dynamics, dynamical systems theory, networked control systems, event-based control, discrete-event systems, or theoretical computer science is not a requirement, but it is an advantage.</li>
</ul>
TU Delft (Delft University of Technology)
Working at TU Delft means contributing to solutions that really make a difference.
For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow.
These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.
At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional.
Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.
Faculty Mechanical Engineering
From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms, research and education at the ME faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems.
ME is a dynamic and innovative faculty with high-tech lab facilities and international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME’s outstanding, state-of-the-art education, which trains students to become responsible and socially engaged engineers and scientists. We translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well-being. That is what unites us in pioneering research, inspiring education and (inter)national cooperation.
Click here to go to the website of the Faculty of Mechanical Engineering. Do you want to experience working at our faculty? These videos will introduce you to some of our researchers and their work.
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 €3204 - €4051 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
For more information about the vacancy, please contact Dr.Gabriel Gleizer, <a href="mailto:G.Gleizer@tudelft.nl" rel="nofollow noopener" target="_blank">G.Gleizer@tudelft.nl</a>.
For more information about the application procedure, please contact Giedo Kocken, HR Advisor, <a href="mailto:recruitment-me@tudelft.nl" rel="nofollow noopener" target="_blank">recruitment-me@tudelft.nl</a>.
Application procedure
Are You Interested In This Vacancy? Please Apply No Later Than 23 October 2026 Via The Application Button And Upload The Following Documents
<ul>
<li>A curriculum vitae (CV) that states your education and relevant working experience.</li>
<li>A brief cover letter describing your interest and background in the topic (no more than 1 page).</li>
<li>One or two research-oriented documents written by you (e.g., MSc thesis, journal/conference publication, project report).</li>
<li>Transcript for your BSc and MSc degrees including grades for courses.</li>
</ul>
You can address your application to Dr.Gabriel Gleizer.
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
<ul>
<li>You can apply online. We will not process applications sent by email and/or post.</li>
<li>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.</li>
<li>Please do not contact us for unsolicited services.</li>
</ul>

PhD Position Chaotic Sampling for Secure and Sustainable Networked Control Systems

PhD Position Chaotic Sampling for Secure and Sustainable Networked Control Systems

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