Reliability Expert for Energy Storage Battery System

Ampace (新能安) is a global battery-technology company specializing in lithium-ion cells and systems for energy storage, data centers, and critical power. Our R&D pairs advanced cell chemistry with semi-solid-state technology to deliver safe, high-performance batteries at scale. This position is based at our R&D center in Xiamen, China.

Responsibilities:

1. Build a cell-to-system reliability simulation framework coupling electrochemical, thermal, mechanical, aging, and system-condition analysis.

2. Develop life and degradation models covering capacity fade, resistance growth, balancing failure, thermal-runaway risk, and consistency degradation.

3. Identify, calibrate, and validate model parameters against lab, test, and field data, with uncertainty analysis.

4. Build digital-twin and surrogate models for life prediction, risk early-warning, and design optimization.

5. Support reliability assessment and accelerated-life-test design from cell to module, pack, and container level.

6. Partner with R&D, test, quality, process, and product teams to turn simulation results into design rules.

Requirements:

1. PhD in reliability engineering, electrochemistry, materials, mechanical, automation, thermal, or computational modeling.

2. Experience in Li-ion or energy-storage reliability, life modeling, degradation mechanisms, thermal safety, or multiphysics simulation.

3. Familiarity with at least one modeling method: equivalent-circuit, single-particle, P2D/DFN, thermal, mechanical, or system-level simulation.

4. Ability to connect battery testing, BMS data, operating conditions, and failure modes into mechanistic insight.

5. Strong English research and technical communication for work with global teams.

Preferred:

1. Cross-scale, cell-to-system modeling experience; UPS energy-storage project experience.

2. Machine learning, Bayesian inference, digital-twin, or uncertainty-quantification experience.

3. Background with a recognized reliability-engineering platform such as Maryland CALCE / CRR; patents, publications, or standards work.

新能安（Ampace）是一家全球领先的电池科技企业，专注于锂离子电芯及电池系统的研发与制造，产品广泛应用于储能、数据中心及关键电源等领域。公司结合先进的电芯化学体系与半固态电池技术，致力于打造兼具高安全性、高性能和规模化生产能力的电池产品。

本岗位工作地点位于中国厦门研发中心。

岗位职责

1. 搭建覆盖电芯到系统层级的可靠性仿真体系，构建融合电化学、热学、力学、老化机理及系统工况分析的多物理场耦合模型。
2. 建立电池寿命与退化模型，研究容量衰减、内阻增长、电芯均衡失效、热失控风险及一致性退化等关键失效机理。
3. 基于实验室测试、可靠性测试及实际运行数据，对模型参数进行辨识、标定与验证，并开展不确定性分析。
4. 开发数字孪生模型及代理模型（Surrogate Model），应用于寿命预测、风险预警及产品设计优化。
5. 支持从电芯、模组、电池包到储能集装箱系统的可靠性评估及加速寿命试验设计。
6. 与研发、测试、质量、工艺及产品团队紧密协作，推动仿真分析成果转化为产品设计规范和工程应用。

任职要求

1. 可靠性工程、电化学、材料科学、机械工程、自动化、热能工程、计算建模等相关专业博士学历。
2. 具备锂离子电池或储能系统可靠性研究经验，熟悉寿命建模、退化机理、热安全分析或多物理场仿真。
3. 熟悉至少一种电池建模方法，包括等效电路模型（ECM）、单颗粒模型（SPM）、P2D/DFN电化学模型、热模型、力学模型或系统级仿真模型。
4. 能够结合电池测试数据、BMS运行数据、实际工况及失效模式，开展机理分析并建立可靠性模型。
5. 具备良好的英文文献阅读、科研交流及技术沟通能力，能够与国际团队开展协作。

优先条件

1. 具备电芯到系统（Cell to System）跨尺度建模经验，或UPS储能系统相关项目经验者优先。
2. 熟悉机器学习、贝叶斯推断、数字孪生或不确定性量化（Uncertainty Quantification）等相关技术者优先。
3. 具有国际知名可靠性研究平台（如 Maryland CALCE、CRR）相关研究背景，或拥有相关专利、学术论文及标准制定经验者优先。