Kaihang Shi

The University at Buffalo is seeking a strong PhD candidate to join the research groups of Prof. Kaihang Shi and Prof. Jiayu Peng. The position focuses on interdisciplinary research at the intersection of artificial intelligence/machine learning (AI/ML), materials science, and chemical engineering. The successful candidate will work on computational methods aimed at accelerating scientific discovery, leveraging data science and advanced computational techniques. This opportunity is part of UB's Computational and Data-Enabled Sciences (CDES) 3-year PhD program, which emphasizes interdisciplinary collaboration and innovative research. Applicants should already possess a Master's degree and demonstrate a keen interest in computational approaches to scientific problems. The program is designed for students excited about working across traditional boundaries in AI/ML, materials science, and chemical engineering. Prospective students are encouraged to mention both Prof. Shi and Prof. Peng in their application materials. For more information about the CDES PhD program, visit the official program page. The application deadline for Fall 2026 is approaching, so interested candidates should act promptly. Funding details are not specified in the announcement; applicants may contact the supervisors or consult the program website for further information. For questions or to discuss research opportunities, candidates are invited to reach out to the supervisors. This is an excellent opportunity for those passionate about computational science and interdisciplinary research in a leading US institution.

The Shi group at the University at Buffalo is seeking motivated Postdoctoral Associates in the Department of Chemical and Biological Engineering. This opportunity is ideal for candidates interested in computational and theoretical chemical engineering, with a focus on generative machine learning, machine learning force fields, and their applications in metal-organic frameworks (MOFs) and polymer membranes. The research will involve developing simulation algorithms and software to model gas adsorption behavior in porous materials, creating novel machine learning models for predicting gas adsorption, and investigating molecular transport and separation mechanisms for membrane processes. Applicants should have a PhD in Chemical Engineering, Materials Science, or a related field, with expertise in at least one of the following: quantum mechanics, molecular simulation, or machine learning (preferably generative AI). A strong publication record and the ability to work independently are preferred. The position offers a competitive salary of $52,000 per year and a comprehensive benefits package, including health and retirement plans. The University at Buffalo is a leading public research university and a flagship of the State University of New York system, recognized for its excellence and impact in research and education. The Shi group is dedicated to advancing the field of computational chemical engineering through innovative research in machine learning and materials simulation. The successful candidate will have the opportunity to publish journal articles, present at professional conferences, and contribute to cutting-edge research in gas adsorption and membrane processes. The University at Buffalo provides a supportive environment for professional growth and development, with resources for career coaching and training. To apply, candidates should submit a cover letter and curriculum vitae through the University at Buffalo job portal. One reference is required. The application deadline is March 20, 2026. For more information about the Shi group and the Department of Chemical and Biological Engineering, visit the university's website.

The Shi group at the University at Buffalo is seeking a motivated Postdoctoral Associate to join their research team in the Department of Chemical and Biological Engineering. This position focuses on the intersection of chemical engineering, machine learning (including generative AI), and molecular simulation, with applications in metal-organic frameworks (MOFs) and polymer membranes. The successful candidate will develop simulation algorithms and software to model gas adsorption behavior in porous materials, create novel machine learning models for predicting gas adsorption, and investigate molecular transport and separation mechanisms for membrane processes. Applicants should have a PhD in Chemical Engineering, Materials Science, or a related field, with expertise in at least one of the following: quantum mechanics, molecular simulation, or machine learning. A strong publication record and the ability to work independently are preferred. The position offers a competitive salary of $52,000 per year and a comprehensive benefits package, including health and retirement plans. The University at Buffalo is a leading public research university and a flagship of the State University of New York system, providing a vibrant academic environment and excellent resources for professional development. The application deadline is March 20, 2026. To apply, submit a cover letter and CV through the UBJobs portal. For more information, contact Assistant Professor Kaihang Shi at [email protected]. This is an excellent opportunity for researchers interested in advancing the fields of chemical engineering, machine learning, and materials science, particularly in the context of MOFs and polymer membranes.