Hybrid Physics-ML Fault/Attack-Tolerant Control with Probabilistic Guarantees

Organisation/Company

Eindhoven University of Technology

Department

Mechanical Engineering

Research Field

Engineering » Control engineering

Researcher Profile

First Stage Researcher (R1)

Positions

PhD Positions

Application Deadline

8 May 2026 - 23:59 (UTC)

Country

Netherlands

Type of Contract

Temporary

Job Status

Full-time

Is the job funded through the EU Research Framework Programme?

Horizon Europe - MSCA

Is the Job related to staff position within a Research Infrastructure?

No

Modern CPSs—such as industrial automation systems, autonomous platforms, and critical infrastructure—are increasingly exposed to cyber-physical attacks and uncertainties. These disturbances induce complex, time-evolving performance degradation that requires tightly integrated approaches combining control, learning, and uncertainty quantification.

This project develops a data-driven control framework grounded in first-principles models with emphasis on:

• Data-driven practical feedback linearization, enabling control of nonlinear systems under uncertainty and partial model knowledge,
• Learning dynamics within control loops, integrating adaptive and optimization-based updates (e.g., stochastic gradient methods and Bayesian learning),
• Probabilistic performance guarantees, leveraging tools from stochastic systems, RKHS-based learning, and Bayesian inference to certify performance and quantify uncertainty,
• Attack-tolerant and resilient control design, explicitly accounting for disturbances, adversarial inputs, and model mismatch,

• Hybrid physics–ML monitoring mechanisms to support detection and isolation when required.

   

Research Objectives

The successful PhD candidate will work on:

• Data-driven nonlinear control under uncertainty
• Developing control strategies based on practical feedback linearization with limited or imperfect models.
• Learning-enabled control dynamics
• Embedding optimization and learning algorithms (e.g., SGD, Bayesian updates) into control design and analysis.
• Attack-tolerant resilient control
• Designing controllers that maintain performance under faults and cyber-physical attacks.
• Probabilistic guarantees and uncertainty quantification
• Establishing guarantees on stability, safety, and performance using RKHS-based methods, stochastic analysis, and Bayesian frameworks.
• Supporting monitoring mechanisms
• Designing anomaly detection tools that complement control strategies when required.

Are you passionate about mathematical systems and control theory? Do you want to develop cutting-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to apply for a PhD position in the SecReSy4You Doctoral Network, a European Union-wide Doctoral Network funded by the Marie Skłodowska-Curie Actions (MSCA). This advertisement focuses on the position (DC10) hosted at the Dynamics and Control section, Department of Mechanical Engineering, Eindhoven University of Technology, the Netherlands. For a complete list of available positions, please visit the network’s website http://www.secresy4you.eu .

Website

https://www.tue.nl/en/working-at-tue/vacancy-overview/phd-on-secresy4you-hybrid…

Research Field

Engineering » Control engineering

Education Level

Master Degree or equivalent

• A master’s degree (or an equivalent university degree) in systems and control, mechanical engineering, electrical engineering or applied mathematics.
• The MSCA mobility rule requires applicants to not have resided or carried out their main activity (work, studies, etc.) in the country of their host organization for more than 12 months in the 3 years immediately prior to the recruitment date.
• Strong background in mathematical systems and control theory.
• Keen interest in hybrid dynamical systems, control and cyber security.
• Knowledge of at least one programming language: Matlab, Python, is expected.
• Eager to work within a team and independently.
• Ability to collaborate with industry and academic researchers.
• Fluent in spoken and written English.

Languages

ENGLISH

Level

Good

Website for additional job details

https://www.tue.nl/en/working-at-tue/vacancy-overview/phd-on-secresy4you-hybrid…

Number of offers available

1

Company/Institute

Eindhoven University of Technology

Country

Netherlands

Geofield

State/Province

Noord Brabant

City

Eindhoven

Website

http://tue.nl

Street

PO Box 513

Postal Code

5600BM

E-Mail

c.g.murguia@tue.nl

Phone

0642248780

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