Funded PhD Position in Multi-Agent AI and Distributed Optimization for Resilient Cyber-Physical Systems. Universidad Rey Juan Carlos, Móstoles, Madrid, Spain. Competitive funding for three years

We are seeking a motivated PhD candidate to join our Artificial Intelligence Group (GIA) and conduct research at the intersection of multi-agent systems, mathematical optimization and machine learning.

Under the supervision of Prof. Marin Lujak, the successful candidate will investigate how autonomous agents can adapt both their operational decisions and their coordination mechanisms as demands, resources and communication conditions change.

The research will draw on two complementary projects:

- CEFIR: intelligent coordination of waste-collection fleets, integrating operational data into dynamic task allocation and vehicle routing.
- CRISIS: coordination of resources during floods and wildfires, addressing uncertainty, disrupted communications and time-critical decisions.

The thesis will develop a focused scientific contribution within this programme, combining methodological advances with evaluation against concrete operational challenges. Its precise scope will be defined with the selected candidate, taking their background and research interests into account.

Your research activities

- Formulate mathematical models for multi-agent coordination, resource allocation and routing, and develop distributed or decentralized solution methods.
- Investigate which decisions require revision after a disruption and how agents should adapt their information exchange and coordination structure.
- Explore how learning and optimization can work together to improve decisions while respecting operational constraints.
- Implement algorithms and design reproducible computational experiments using simulation and digital twins.
- Contribute to scientific publications and collaborate with academic and project partners.

Candidate profile

We welcome applications from candidates with:





- A Master’s degree in Computer Engineering, Artificial Intelligence, Operations Research, Applied Mathematics or a related discipline.
- Solid foundations in mathematical modelling, algorithms and optimization.
- Good programming skills, preferably in Python.
- Proficiency in written and spoken English.
- Intellectual curiosity, analytical rigour and the ability to work both independently and collaboratively.

Experience with Gurobi, multi-agent systems, distributed computing, simulation or machine learning would be an advantage.

What the position offers The position combines three years of competitive funding with scientific supervision and opportunities to develop original research connecting AI and Operations Research in a competitive international environment. The candidate will work on problems arising in industrial fleet management and crisis response, with opportunities to collaborate with industrial and academic project partners and contribute to scientific publications.

How to apply

Please email one PDF containing your detailed CV, a motivation letter and academic transcripts to marin dot lujak at urjc dot es .

Email subject: PhD application – CEFIR/CRISIS

Your motivation letter should explain your relevant experience, your interest in the position and the research questions you would like to explore. Links to research code or publications are welcome, if available.

About the university

@Universidad Rey Juan Carlos (URJC) is the most modern public university and one of the largest in the Madrid region in Spain. As a part of the EULIST Alliance, its teaching and research span multiple disciplines, with international collaboration across academic institutions, industry and public organizations to address scientific and societal challenges.

Please share this opportunity with students and colleagues who may be interested.

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📌 Funded PhD Position in Multi-Agent AI and Distributed Optimization for Resilient Cyber-Physical Systems (Móstoles)
🏢 Universidad Rey Juan Carlos
📍 Móstoles