PhD: Fair, Scalable Distributed Optimization for Large Networks

TUE; Eindhoven; On-site; EUR 36,000 - 45,000; Full time

Benefits offered by this job

ABP pension scheme

Free 24/7 OpenUp mental health support

Commuting/Internet cost allowance

On-campus day care

Job summary

TU/e is seeking a PhD candidate in Fair Distributed Optimization and Control of Large-Scale Networked Systems. You will develop scalable multi-agent algorithms with fairness built in, embedding fairness constraints into optimization and control for electricity distribution networks.

The project uses distributed optimization, stochastic/robust methods, and proofs of convergence and fairness. Collaboration with energy experts will accompany your research journey at TU/e.

Qualifications

• Master's degree or equivalent in a related field.
• Strong background in control theory and/or optimization.
• Programming experience (Python, MATLAB or Julia).
• Fluent in spoken and written English (C1).
• Ability to work in an interdisciplinary team.

Responsibilities

• Formulate fair resource allocation problems for large-scale networks.
• Design distributed optimization algorithms coordinating thousands of agents.
• Develop fairness-aware feedback controllers maintaining scalability and stability.
• Analyze probabilistic allocation policies and their fairness.
• Prove theoretical guarantees and test on realistic network data.

Skills

Control theory

Optimization

Applied mathematics

Education

Master's degree in Systems and Control / Electrical Engineering / Applied Mathematics

Tools

Python

MATLAB

Julia

Job description

TU/e is seeking a PhD candidate in Fair Distributed Optimization and Control of Large-Scale Networked Systems. You will develop scalable multi-agent algorithms with fairness built in, embedding fairness constraints into optimization and control for electricity distribution networks.

The project uses distributed optimization, stochastic/robust methods, and proofs of convergence and fairness. Collaboration with energy experts will accompany your research journey at TU/e.