Research Assistant - – Battery Analytics & AI Modeling

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

Research Assistant - – Battery Analytics & AI Modeling

Research Assistant – Battery Analytics & AI Modeling at Volta Digital Energy Technology Limited, focusing on full-lifecycle battery asset health and digital energy risk management. The role involves physics-informed AI modeling, battery diagnostics, and energy storage digital asset solutions across Hong Kong, Mainland China, and international markets.

Key responsibilities

Collect dynamic operational time-series data (voltage, current, temperature) from pilot EV charging networks and energy storage systems

Conduct millivolt-level (mV) micro-voltage curve cleaning, filtering, and statistical feature extraction to support P2D electrochemical model parameter inversion

Assist in the maintenance and optimization of the Volta-Guard engine and structural "fault-phenomenon-mechanism" knowledge graph

Implement statistical learning, Gaussian Processes, and uncertainty quantification methods to train battery State of Health (SOH) and Remaining Useful Life (RUL) estimation models

Support early identification of battery "sub-health" degradation states (e.g., lithium dendrite formation, internal micro-short circuits) for multi-week advance risk warning

Execute technical deliverables and data analysis tasks under the HSITPL Incubation Support Programme and accelerator milestones

Assist in formatting technical testing protocols aligned with international battery second-life standards (UL 1974:2023 Annex D) and national standards (GB/T) to generate standard digital battery health reports

Assist in interfacing battery health profile datasets with downstream insurance dynamic pricing models (UnderwriteAI™) and energy storage on-chain data verification frameworks

About you

Bachelor's degree or above (Master's / Ph.D. candidate preferred) in a STEM discipline (Data Science, Computer Science, Information Engineering, Electrical Engineering, Applied Mathematics, Physics, Energy Systems, or related fields)

Proficiency in Python, R, or MATLAB for big data analytics, numerical simulation, and machine learning/deep learning workflows

Sound understanding of time-series analysis, Gaussian Process regression, optimization methods, or battery degradation mechanisms

Familiarity with electrochemical impedance spectroscopy (EIS), battery charging curves, or BMS telemetry data is a strong advantage

Experience in blockchain data analytics, DeFi/Web3 smart contracts, or InsurTech modeling is a plus

Strong research, problem-solving, and algorithmic implementation capabilities

High proficiency in written and spoken English and Chinese (Cantonese and/or Putonghua)

15 working days paid annual leave, plus Hong Kong statutory holidays

Discretionary Performance Bonus based on R&D project achievements

Working Hours: Monday to Friday, 9:00 a.m. – 6:00 p.m.

About us

Volta Digital Energy Technology Limited is an approved incubatee under the Hong Kong-Shenzhen Innovation and Technology Park (HSITPL) Incubation Support Programme. Focusing on full-lifecycle battery asset health and digital energy risk management, Volta pioneers physics-informed AI modeling (P2D electrochemical model and Volta-Guard AI Battery Knowledge Graph) and microsecond pulse rejuvenation. We provide zero-retrofit diagnostic solutions (DaaS), InsurTech risk quantification (UnderwriteAI™), and energy storage digital asset bankability infrastructure across Hong Kong, Mainland China, and international markets.