"PhD on Intelligent data-driven charge management system for future electrified mobility"

Job Summary

We are seeking a highly motivated PhD candidate to develop AI-driven solutions for sustainable mobility, focusing on intelligent charge management systems for electric vehicles. The research integrates AI, optimization, and energy management to address challenges in electrified mobility.

Responsibilities

• Develop smart and early anomaly detection using probabilistic AI models, transfer learning, and semi-supervised learning.
• Create accurate energy consumption and demand predictions with advanced neural architectures and hybrid models.
• Optimize multi-vehicle dynamic wireless power transfer (DWPT) charging using reinforcement learning and model predictive control.
• Evaluate and validate system performance through simulations, Hardware-in-the-Loop setups, and industry collaborations.

Qualifications and Requirements

• Master’s degree in systems and control, mechanical engineering, electrical engineering, data science, or applied mathematics.
• Strong background in data-based learning techniques or systems and control theory.
• Affinity with electric vehicles and knowledge of programming languages like MATLAB/Simulink and Python.
• Experience or interest in systems and control, with eagerness to work in an interdisciplinary team.
• Willingness to travel to industry partners and fluency in English.

What the Employer Offers

• Full-time, four-year fixed-term contract with a salary range of €3,059 to €3,881 per month.
• Opportunities for teaching (10-15% of time), training programs, and collaboration with international researchers.
• Benefits including pension scheme, vacation pay, year-end bonus, and support for commuting and relocation.
• Work in a dynamic university environment with access to advanced technical infrastructure.