Arbetsbeskrivning

In this role, you will contribute to building next-generation capabilities for assessing battery health and lifetime, enabling smarter decisions across the lifecycle of electric vehicles—from first use to second-life applications.

You will work closely with experts in data science, software, and engineering, bringing critical domain knowledge to ensure that battery insights are technically sound, interpretable, and actionable.

What You Will Do

Develop and validate methods for State of Health (SOH) and Remaining Useful Life (RUL) estimation for Li-ion batteries

Analyze real-world vehicle and battery data to understand degradation behavior over time

Interpret and explain battery aging based on factors such as:

• Temperature
• State of Charge (SOC)
• Depth of Discharge (DoD)
• Charging patterns and C-rate

Load profiles and usage conditions

Compare and evaluate on-board BMS health estimates vs. off-board analytical models

Define confidence levels, limitations, and applicability of lifetime predictions

Collaborate with cross-functional teams to ensure models are physically grounded and credible

Translate battery health insights into practical recommendations for:

• Lifecycle planning
• Residual value and risk assessment
• Warranty and service strategies
• Second-life and reuse scenarios

What We Are Looking For

Strong background in Li-ion battery technology and degradation mechanisms

Experience with battery lifetime assessment, including:

• Calendar aging
• Cycle aging
• Real-world usage effects

Deep understanding of:

• SOH and RUL
• Capacity fade and resistance increase
• Performance degradation in field conditions

Experience working with battery data from vehicles, BMS systems, or testing environments

Ability to critically evaluate models and challenge assumptions

Experience collaborating with data scientists, engineers, and business stakeholders

Strong communication skills—able to explain complex battery behavior clearly

Meriting Experience

Experience with battery systems in electric vehicles (BEVs)

Exposure to second-life, residual value, or warranty risk analysis

Experience comparing BMS estimates with external models

Basic ability to work with Python, SQL, or similar tools

Background in high-utilization or commercial vehicle applications

Education

Degree in electrochemistry, battery technology, electrical engineering, materials science, or similar

Advanced studies within energy storage systems are a plus

Why Multiply

Work on real-world electrification challenges with direct impact on sustainability and lifecycle efficiency

Combine deep engineering knowledge with data-driven decision-making

Collaborate in cross-functional teams spanning software, data, and systems engineering

Contribute to building scalable capabilities for next-life battery use and optimization