Organisation/Company Universitat Politècnica de València Department Instituto Universitario de Automática e Informática Industrial Research Field Engineering » Control engineering Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions Application Deadline 15 Dec 2026 - 23:59 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Full-time Hours Per Week 35 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Project Title: Graph Neural Network-Based Conditional Multi-Agent Control Architecture for the Optimal Operation of Urban Energy Communities (MAC4CE)

Position Overview

The Instituto Universitario de Automática e Informática Industrial (ai2) at UPV is seeking a highly motivated and talented Postdoctoral Researcher to join the MAC4CE project. This ambitious 4-year initiative sits at the cutting-edge intersection of Industrial Engineering, Advanced Control Systems, and Artificial Intelligence.

The successful candidate will lead the development of a novel distributed control framework. This architecture leverages Graph Neural Networks (GNNs) and Multi-Agent Reinforcement Learning (MARL) to optimize the real-time operations, energy routing, and flexibility of complex Urban Energy Communities.

Key Responsibilities

- Design and implement scalable MARL algorithms combined with GNN architectures to model power grid topologies and spatial dependencies.
- Develop advanced mathematical optimization models for conditional control within multi-agent energy environments.




- Build simulation environments and validate algorithms using Python, MATLAB, or specialized power system co-simulation tools.
- Co-author high-impact journal publications (IEEE, Elsevier, etc.) and present research findings at top-tier international conferences (NeurIPS, ICML, IEEE CSS/PES).
- Contribute to mentoring PhD candidates and junior researchers within the group.

Key Requirements & Qualifications

- Education: A Ph.D. in Industrial Engineering, Electrical Engineering, Automation/Control Engineering, Computer Science, or a closely related STEM field.
- Core Technical Skills: Strong background in advanced control theory, mathematical optimization, and deep learning architectures (specifically Neural Networks).
- Specialized Expertise: Proven research experience in Reinforcement Learning (ideally Multi-Agent settings) and Graph Neural Networks (GNNs).
- Software Proficiency: Advanced programming skills in Python (PyTorch, TensorFlow) and/or MATLAB / Simulink.
- Language: Excellent written and oral communication skills in English. (Knowledge of Spanish is NOT required for this research position).

What We Offer

- Stability & Funding: A long-term 3.5-year contract providing a clear runway for academic and professional growth with a highly competitive salary up to €45,000.




- Ecosystem: Work at one of Spain’s premier automation and computer science institutes, embedded in a vibrant, international research community.
- Mobility Package: Full funding for high-performance computing resources, international research stays, and attendance at top international conferences.
- Quality of Life: Live and work in Valencia, a world-class Mediterranean city renowned for its exceptional quality of life, safety, and cultural environment.

Where to apply

E-mail [email protected]

Requirements

Research Field Engineering » Control engineering Education Level PhD or equivalent

Research Field Engineering » Computer engineering Education Level PhD or equivalent

Research Field Engineering » Industrial engineering Education Level PhD or equivalent

Research Field Engineering » Electrical engineering Education Level PhD or equivalent

Research Field Engineering » Mechanical engineering Education Level PhD or equivalent

Skills/Qualifications

Key Requirements & Qualifications

- Education: A Ph.D. in Industrial Engineering, Electrical Engineering, Automation/Control Engineering, Computer Science, or a closely related STEM field.
- Core Technical Skills: Strong background in advanced control theory, mathematical optimization, and deep learning architectures (specifically Neural Networks).
- Specialized Expertise: Proven research experience in Reinforcement Learning (ideally Multi-Agent settings) and Graph Neural Networks (GNNs).
- Software Proficiency: Advanced programming skills in Python (PyTorch, TensorFlow) and/or MATLAB /

📌 3.5-Year Postdoctoral Research Position in AI (España)
🏢 Universitat Politècnica de València
📍 España