岗位描述
Responsibilities / 工作职责： Develop and optimize MD workflows for electrolytes, interfaces, and polymer systems.搭建并优化电解液、界面与聚合物体系的分子动力学（MD）模拟流程。Build top-down fitting pipelines to calibrate force-field/CG parameters against target observables.开发 top-down fitting 流程，基于目标指标对力场/粗粒化参数进行拟合与迭代优化。Develop and integrate machine-learning force fields / ML interatomic potentials when appropriate.开发并在需要时集成机器学习势（ML force field / ML interatomic potential）到模拟工作流中。 Ensure modular, efficient, reproducible code and maintain clear documentation.保证代码模块化、高效、可复现，并维护清晰文档。 Qualifications / 任职要求：● PhD or equivalent or related working experience in Materials/ Chemistry/Physics/ Biology/Engineering/CS/AI or related fields.材料/化学/物理/生物/工程/计算机/AI 等相关方向博士或同等相关领域工作经验。 Hands-on experience with MD (e.g., GROMACS/LAMMPS/OpenMM) and trajectory analysis.具备 MD 实操经验（如 GROMACS/LAMMPS/OpenMM）及轨迹分析能力。Strong Python skills; experience with ML frameworks is a plus.Python 编程能力强；有机器学习框架经验者加分。Experience with ML force fields / GNN/equivariant models is preferred.有机器学习势或 GNN/等变模型经验者优先。Good professional English communication and strong problem-solving skills.具备良好的英文沟通能力与问题解决能力。