Research Assistant — Battery AI Modeling & Health Analytics

Volta Digital Energy Technology Limited; Hong Kong; On-site; HKD 180,000 - 240,000; Full time

Benefits offered by this job

15 days paid annual leave

Discretionary bonus

Job summary

Volta Digital Energy Technology Limited is seeking a Research Assistant to advance battery analytics and AI-based modeling across Hong Kong, Mainland China and international markets. The role focuses on full-lifecycle battery health, physics-informed AI, and risk assessment of energy storage assets.

Ideal candidates hold a STEM degree and are proficient in Python, R, or MATLAB, with experience in time-series data, Gaussian processes, or BMS telemetry.

Qualifications

• Bachelor's degree or above in STEM fields.
• Master's/PhD candidate preferred.
• Proficiency in Python, R or MATLAB for analytics.

Responsibilities

• Collect dynamic time-series data from pilot EV charging networks and energy storage systems.
• Perform mV-level curve cleaning, filtering and feature extraction for model inversion.
• Maintain and optimize the Volta-Guard engine and knowledge graph.
• Apply ML/GP methods to train SOH and RUL models.
• Identify early sub-health degradation states for risk warnings.
• Deliver technical tasks under HSITPL Incubation milestones.
• Interface battery health data with insurance pricing models and on-chain verification.

Skills

Python

R

MATLAB

Time-series analysis

Gaussian Processes

Uncertainty quantification

Machine learning

Deep learning

English proficiency

Cantonese/Putonghua

Problem-solving

Education

Bachelor's degree in STEM

Master's/PhD candidate preferred

Tools

Volta-Guard engine

bms telemetry

Job description

Volta Digital Energy Technology Limited is seeking a Research Assistant to advance battery analytics and AI-based modeling across Hong Kong, Mainland China and international markets. The role focuses on full-lifecycle battery health, physics-informed AI, and risk assessment of energy storage assets.

Ideal candidates hold a STEM degree and are proficient in Python, R, or MATLAB, with experience in time-series data, Gaussian processes, or BMS telemetry.