摘要：康奈尔大学（Cornell University），坐落于美国纽约州，是世界顶尖的私立研究型大学。作为著名的常春藤联盟成员，康奈尔大学由埃兹拉·康奈尔（Ezra Cornell）与安德鲁·怀特于1865年创立。它是八所常春藤学府中唯一创办于美国独立战争之后的院

康奈尔大学（Cornell University），坐落于美国纽约州，是世界顶尖的私立研究型大学。作为著名的常春藤联盟成员，康奈尔大学由埃兹拉·康奈尔（Ezra Cornell）与安德鲁·怀特于1865年创立。它是八所常春藤学府中唯一创办于美国独立战争之后的院校，其开创性的办学理念对美国高等教育产生了深远影响。康奈尔大学建立之初，规模是当时全美高校中之最。其办学宗旨为提供平等的教育机会给每一个人，是常春藤联盟中第一所男女合校实施性别平等的大学，也是最早在招生时不计贵族身份、不分信仰和种族的高等学府。康奈尔大学致力于创设一所学科齐全、包容性强的新型综合性大学。在工程、材料、计算机与信息科学、农业与生命科学、建筑等专业领域，康奈尔大学均名列世界前茅。

Cornell University, founded in 1865, is a world-renowned Ivy League institution located on a beautiful 750-acre campus. The university offers a unique combination of private school education, including top-ranked engineering programs, and a federal land-grant institution with nationally-ranked programs in agriculture and life sciences, among others. Cornell is committed to promoting interdisciplinary research and scholarship and actively encourages diversity, equity, and inclusion in its hiring process.

康奈尔大学 PEESE 团队（www.peese.org）现招聘2-3个博士后研究职位，该职位由康奈尔大学 Cornell AI for Sustainability Initiative (CAISI)和Cornell University AI for Science Institute (CUAISci)支持和资助。博士后研究员将参与人工智能与材料科学交叉领域的前沿研究，解决可持续材料设计等领域的全球性挑战。候选人将与顶尖的研究人员密切合作，利用康奈尔大学的先进设施和硬件资源，在跨学科中推动AI for Materials Informatics及相关领域的变革性发展。

更多详情请访问：

CAISI：https://sustainability.ai.cornell.edu

CUAISci：http://science.ai.cornell.edu

1. 设计与优化：运用先进的计算模拟方法，如高通量第一性原理计算和分子动力学，系统优化材料的结构和性能，提供针对性设计方案，助力突破材料研发瓶颈。

2. 高通量材料筛选：通过大规模理论计算，快速筛选出适合多领域应用的优质材料（如电池系统、超级电容器、催化剂、光伏设备等），以提升研发效率，加速可持续材料的开发进程。

3. 基于机器学习的材料逆向设计：构建和应用机器学习及深度学习模型，精准预测材料的关键性能指标（如热力学稳定性、导电性、机械强度及光学性能）。结合模型分析，揭示材料性能的潜在驱动因素，实现材料成分和结构的逆向设计，推动从经验驱动到数据驱动的材料研发范式转变。

4. 材料生成式模型开发：利用生成式人工智能进行新材料的自动生成与探索。借助该技术挖掘潜在的高性能材料，拓展材料科学研究的边界，引领未来材料研发的新方向。

符合条件的候选人将有机会被推荐为康奈尔大学的 AI4S 博士后研究员，借助 CAISI 平台（https://sustainability.ai.cornell.edu/ai4s-postdoc）深入参与跨学科研究与合作。

有意者请将详细的个人简历（CV）通过邮件发送至 Fengqi You 教授（fengqi.you@cornell.edu）。请在邮件主题中注明：“AI4S Postdoc Position”。

我们诚邀具备相关研究背景的研究人员，共同推进材料信息学与计算材料学的前沿研究。特别欢迎在AI for Materials领域具备深厚专业知识与技术储备的申请者加入。

AI4S Postdoctoral Research Associates at Cornell University (Ithaca, New York)

Dear Colleagues,

The PEESE group at Cornell University (www.peese.org) invites applications for 2-3 postdoctoral research positions. These roles are part of our efforts within the Cornell AI for Sustainability Initiative(CAISI, https://sustainability.ai.cornell.edu/) and theCornell University AI for Science Institute(CUAISci, http://science.ai.cornell.edu).

This is an exciting opportunity for postdoctoral researchers to engage in cutting-edge research at the intersection of AI and materials science, addressing urgent global challenges in sustainable materials development and beyond. Candidates will work closely with leading researchers in an interdisciplinary environment, leveraging state-of-the-art facilities and resources at Cornell to drive transformative advancements inAI for Materials Informaticsand related areas:

• Materials Design and Optimization: Utilize advanced computational methods, such as high-throughput first-principles calculations and molecular dynamics, to systematically optimize material structures and properties, providing tailored solutions to overcome material development challenges.

• High-Throughput Computational Materials Screening: Conduct large-scale theoretical simulations to efficiently identify high-performance materials suitable for diverse applications, including battery systems, supercapacitors, catalysis, and photovoltaic devices. This accelerates sustainable material development and enhances research productivity.

• Machine Learning Applications in Materials Science: Develop and apply machine learning and deep learning models to accurately predict key material properties (e.g., thermodynamic stability, conductivity, mechanical strength, and optical performance). These models uncover critical physicochemical factors influencing material behavior, enabling inverse design of material compositions and structures to meet specific performance requirements.

• Materials Generative Models: Employ generative AI models, for automated materials generation and exploration. This approach unlocks the potential to discover novel high-performance materials, pushing the boundaries of material science and pioneering the future of material innovation.

Qualified candidates may be recommended for the prestigious AI4S Postdoctoral Associate titleat Cornell University, offering opportunities to further engage in interdisciplinary training and collaboration through CAISI (https://sustainability.ai.cornell.edu/ai4s-postdoc).

We are seeking highly motivated researchers to advance cutting-edge work in Materials Informatics and Computational Materials Sciences. Applicants with strong expertise in AI for materialsare particularly encouraged to apply.

Interested candidates are encouraged to submit a detailed curriculum vitae (CV) via email to Prof. Fengqi You at fengqi.you@cornell.edu. Please include "AI4S Postdoc Position" in the subject line.

Join us at Cornell and contribute to shaping the future of AI-driven sustainability and materials discovery.

Warm regards,

Fengqi You, Ph.D.

Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering

Co-Director, Cornell University AI for Science Institute (CUAISci)

Senior Faculty Fellow, Cornell Atkinson Center for Sustainability

Co-Director, Cornell Institute for Digital Agriculture (CIDA)

Director, Cornell AI for Sustainability Initiative (CAISI)

Elected Fellow of AAAS, AIChE, and RSC

Cornell University

Website: www.peese.org

来源：伟泽教育