3.5-Year Postdoctoral Research Position In Ai

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 *****: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
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
/ Simulink.
Language:
Excellent written and oral communication skills in English. (Knowledge of Spanish is NOT required for this research position).
Languages ENGLISH Level Good
Languages SPANISH Level Basic
Languages CATALAN Lev