Open Positions

PhD POSITION – ELECTRICAL ENGINEERING

Research Area: Intelligent Battery Management System for Battery Energy Storage System (BESS) and Electric Vehicles (EVs)

Position: Ph.D. Research Scholar

Department: Electrical Engineering

We at NextGeAR Lab are looking for a highly motivated, dedicated, self-driven candidate to join as a PhD scholar in Electrical Engineering, focused on the development of advanced battery management systems and intelligent energy-management technologies. The research will involve modelling, characterisation, monitoring, diagnostics, and prediction of rechargeable battery systems, with emphasis on developing reliable and intelligent methods for battery performance evaluation, health assessment, and lifecycle analysis, along with data-driven approaches for understanding degradation and operational behaviour.

The candidate will have the opportunity to work at the intersection of electrical engineering, energy storage, battery management, machine learning, and power-electronic systems, with scope for both experimental and computational research.

Eligibility

Essential:

• Master's degree (M.Tech./M.E. preferred) in Electrical Engineering, Electrical & Electronics Engineering, Electronics & Communication Engineering, Energy Engineering, or a closely related discipline.

• Strong fundamentals in electrical engineering, power systems, power electronics, control systems, or energy-storage technologies.

• Demonstrated interest in research and willingness to work on interdisciplinary problems involving batteries and intelligent computational methods.

Desirable:

• Knowledge of MATLAB/Simulink, Python, or similar scientific-computing tools.

• Familiarity with machine learning/deep learning frameworks and data analysis.

• Prior exposure to lithium-ion batteries, BMS, electric vehicles, energy-storage systems, or battery experimentation.

• Research experience, publications, thesis work, or relevant project experience will be an advantage.

The selected scholar is expected to contribute toward advanced algorithms, battery models, intelligent prognostic methodologies, experimental datasets, and real-time/embedded battery-management solutions, with opportunities for high-quality journal and conference publications and collaboration with academic and industrial research groups.