Reliability Expert for Energy Storage Battery System
Job Description
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.
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Responsibilities:
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1. Build a cell-to-system reliability simulation framework coupling electrochemical, thermal, mechanical, aging, and system-condition analysis.
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2. Develop life and degradation models covering capacity fade, resistance growth, balancing failure, thermal-runaway risk, and consistency degradation.
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3. Identify, calibrate, and validate model parameters against lab, test, and field data, with uncertainty analysis.
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4. Build digital-twin and surrogate models for life prediction, risk early-warning, and design optimization.
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5. Support reliability assessment and accelerated-life-test design from cell to module, pack, and container level.
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6. Partner with R&D, test, quality, process, and product teams to turn simulation results into design rules.
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Requirements:
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1. PhD in reliability engineering, electrochemistry, materials, mechanical, automation, thermal, or computational modeling.
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2. Experience in Li-ion or energy-storage reliability, life modeling, degradation mechanisms, thermal safety, or multiphysics simulation.
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3. Familiarity with at least one modeling method: equivalent-circuit, single-particle, P2D/DFN, thermal, mechanical, or system-level simulation.
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4. Ability to connect battery testing, BMS data, operating conditions, and failure modes into mechanistic insight.
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5. Strong English research and technical communication for work with global teams.
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1. Cross-scale, cell-to-system modeling experience; UPS energy-storage project experience.
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2. Machine learning, Bayesian inference, digital-twin, or uncertainty-quantification experience.
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3. Background with a recognized reliability-engineering platform such as Maryland CALCE / CRR; patents, publications, or standards work.
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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。
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本岗位工作地点位于中国厦门研发中心。
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岗位职责
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- 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。
- 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。
- 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。
- 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。
- 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。
- 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。
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任职要求
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- 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。
- 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。
- 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。
- 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。
- 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。
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优先条件
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- 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。
- 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。
- 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。
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