Fair Optimization & Control for Networked Systems

Departments, Department of Electrical Engineering; Eindhoven; Vor Ort; EUR 36.000 - 45.000; Vollzeit

Benefits dieser Stelle

4-year employment contract

ABP pension scheme

8% holiday allowance

8.3% year-end bonus

On-campus childcare

Zusammenfassung

TU/e Department of Electrical Engineering in Eindhoven invites applications for a PhD position focusing on fair distributed optimization and control of large-scale networked systems. You will design scalable multi-agent algorithms with fairness built in, and test them on realistic electricity distribution networks and real-world data from Dutch system operators.

Strong background in control theory and optimization is required, with a passion for rigorous analysis, probabilistic allocation, and

Qualifikationen

• Background in control theory and optimization is required.
• Strong mathematical skills with rigorous analysis and proofs.
• Fluent English (C1) is required.

Aufgaben

• Formulate fair resource allocation problems for large-scale networks.
• Design distributed optimization algorithms with local information.
• Develop fairness-aware feedback controllers ensuring scalability and stability.
• Analyze probabilistic allocation policies and uncertainty handling.
• Validate methods on simulations and real-world data from Dutch networks.
• Publish results in top control and optimization venues.

Kenntnisse

Control systems

Optimization

Applied mathematics

Multi-agent systems

Fairness notions

Programming (Python/MATLAB/Julia)

English proficiency

Ausbildung

Master’s degree in Systems and Control / related field

Jobbeschreibung

TU/e Department of Electrical Engineering in Eindhoven invites applications for a PhD position focusing on fair distributed optimization and control of large-scale networked systems. You will design scalable multi-agent algorithms with fairness built in, and test them on realistic electricity distribution networks and real-world data from Dutch system operators.

Strong background in control theory and optimization is required, with a passion for rigorous analysis, probabilistic allocation, and