Computational Materials Scientist | 计算材料科学家

Design and automate reproducible, scalable workflows; conduct performance testing and optimization. Analyze simulation outputs to extract physical insights, guiding material design and safety strategies. Any of the following: Perform first‑principles (e.g. DFT) and physics‑based (e.g. MD) simulations to study structural, kinetic, electronic, and thermodynamic properties of battery materials. Develop force fields. Systematically study multiphysics coupling and failure evolution in batteries, including lithium‑ion diffusion, charge transfer, double‑layer effects, aging reactions, and thermal runaway processes (SEI decomposition, separator shrinkage, electrolyte oxidation, cathode/anode heat & gas generation). Build high‑fidelity multiscale models using FEM/numerical tools and physics models（e.g. P2D）, simulating polarization, degradation, and thermal propagation under complex operating conditions. 职责： 设计并自动化高性能计算工作流程，开展性能测试与优化。 分析模拟结果，提取物理学见解，指导材料设计与安全策略。 以下任何一项： 执行第一原理计算（e.g. DFT）和基于物理的模拟（e.g. MD），研究电池材料的结构、动力学、电子与热力学性质。开发动力学力场。 系统研究电池内部的多物理场耦合与失效演化，包括锂离子扩散、电荷转移、双电层效应、老化反应，以及热失控过程中的 SEI 分解、隔膜收缩、电解液氧化、正负极产热与产气。 构建高保真的多尺度模型，使用有限元/数值工具和物理模型（e.g. P2D），模拟复杂工况下的极化、衰减与热蔓延行为。

PhD or equivalent experience in Computer Science, Materials Science, Chemistry, Physics, Electrochemistry, Chemical Engineering, or Engineering Thermophysics. Exceptional Masters will be considered. Strong programming (e.g. Python, C++), scripting (e.g. Bash), and HPC experience is preferred. Strong communication skills, bilingual (Chinese/English), collaborative mindset. Preferred: Publications in top journals/conferences on battery materials, electrochemical modeling, or safety; experience with AI for Science projects; deep knowledge of aging mechanisms (lithium plating, SEI growth, LAM). Any of the following: Expertise in electronic structure theory, quantum chemistry software (VASP, QE, Gaussian, ORCA), and force field modeling (OPLS, AMOEBA). Solid foundation in FEM/numerical modeling. Proficient with COMSOL, ANSYS, MATLAB/Simulink, PyBaMM. Familiarity with experimental principles (ARC, DSC, TGA, EIS, HPPC, GITT). 任职要求： 计算机科学、材料科学、化学、物理、电化学、化学工程或工程热物理等相关领域博士，优秀硕士亦可。 扎实的编程技能（e.g. Python、C++）、脚本技能（e.g. Bash）、HPC 经验优先。 出色的沟通能力，中英文双语，具备协作精神。 优先条件：在电池材料、电化学建模或安全领域发表顶级论文，具备 AI for Science 项目经验，对老化机理（析锂、SEI 生长、活性物质损失）有深入研究。 以下任何一项： l 精通电子结构理论、量子化学软件（VASP、QE、Gaussian、ORCA）及力场建模（OPLS、AMOEBA）。 具备有限元/数值建模基础，熟练使用 COMSOL、ANSYS、MATLAB/Simulink、PyBaMM。 熟悉 ARC、DSC、TGA、EIS、HPPC、GITT 等实验原理