Doctoral Researcher in AI and Quantum-Inspired Optimization for Sustainable Energy Systems
Core
Developing AI-based and quantum-inspired methods for the modelling, optimization, and operation of sustainable multi-energy systems, with a focus on green maritime energy systems.
Role type
Doctoral Researcher (AI and Quantum-Inspired Optimization)
Builds
Scientific publications and validated simulation models for integrated energy systems, green hydrogen, and smart grids.
Domain
Sustainable Energy Systems / AI / Quantum-Inspired Optimization
Deliverable
production ML models | research
Required skills
Mathematical optimization, Machine learning, Reinforcement learning, Data-driven decision-making, Energy-system modelling, Python, MATLAB, Julia
Preferred skills
Stochastic optimization, Robust optimization, Real-time decision-making, Quantum computing, Energy-system simulation tools
Responsibilities
Developing mathematical and AI-based models for sustainable multi-energy systems; Designing optimization methods for system planning and operation; Exploring quantum-inspired optimization methods; Applying methods to case studies (ship/port energy, green hydrogen, smart grids); Implementing algorithms and simulation models; Analysing and validating data; Preparing scientific publications.
Seniority
PhD Candidate, independent researcher