PhD in Chaotic Sampling for Secure Networked Control

Delft; Netherlands; Remote; EUR 36,000 - 45,000; Full time

Benefits offered by this job

Annual leave and pension contributions

Relocation assistance

Possibility of teaching up to 20%

Job summary

TU Delft's Delft Center for Systems and Control invites applications for a PhD position on chaotic sampling for secure and sustainable networked control systems. The project blends mathematical theory with computational methods to design event-based sampling that preserves stability while reducing communication and improving security.

Supervised by Gabriel de Albuquerque Gleizer, the role is theory‑centric with strong publication potential and the option for experimental demonstrations.

Qualifications

• MSc degree in systems & control, electrical engineering, mechanical engineering, applied mathematics, physics or closely related field.
• Strong motivation to conduct theory-driven research and to develop rigorous mathematical arguments.
• Interest in chaos, nonlinear dynamics, and unpredictability.
• Solid foundations in linear algebra and differential equations.
• Proficiency in scientific programming and strong command of English.

Responsibilities

• Develop mathematical theory and computational methods for chaotic sampling in networked control systems.
• Study conditions for chaotic behavior in event-based sampling and design controller/sampler strategies.
• Assess robustness to disturbances and potential learning of transmission patterns from observations.
• Produce theoretical results, proofs, and computational algorithms; contribute open‑source software and simulations.
• Optionally contribute to experimental demonstrations with wireless lab-scale control systems.

Skills

Mathematics

Scientific programming

English proficiency

Abstract thinking

Education

MSc in systems & control or related field

Tools

Python

MATLAB

Simulink

Job description

TU Delft's Delft Center for Systems and Control invites applications for a PhD position on chaotic sampling for secure and sustainable networked control systems. The project blends mathematical theory with computational methods to design event-based sampling that preserves stability while reducing communication and improving security.

Supervised by Gabriel de Albuquerque Gleizer, the role is theory‑centric with strong publication potential and the option for experimental demonstrations.