The Computational Materials Design Laboratory at Konkuk University is recruiting highly motivated graduate students who want to solve important energy and materials challenges through computational chemistry, molecular simulation, and artificial intelligence.
Our laboratory is currently conducting four major government-funded research projects, providing new members with stable research opportunities across AI-driven materials discovery, next-generation batteries, and green hydrogen technologies.
Open Positions
Ph.D. Students
M.S. Students
Pre-admission Researchers
International and domestic applicants are welcome.
Graduate positions | Seoul, South Korea
Future materials researchers need more than expertise in a single simulation method. At CMD Lab, you will develop an integrated research skill set combining:
Density functional theory (DFT)
Molecular dynamics (MD)
Artificial intelligence and machine learning
High-throughput materials screening
Generative and evolutionary materials design
Multiscale and process-level modeling
This combination prepares our members for competitive careers in academia, national research institutes, and technology-driven industries.
Students are trained to move beyond routine calculations and develop complete scientific stories—from defining an important research question to interpreting results and preparing a manuscript.
You will receive close guidance in:
Designing original and publishable research
Interpreting electronic structures and reaction mechanisms
Connecting theoretical predictions with experiments
Preparing figures, manuscripts, and responses to reviewers
Presenting research at conferences and international meetings
Our goal is for each member to grow into an independent computational materials scientist capable of leading high-impact research.
CMD Lab works closely with leading experimental and theoretical research groups in Korea, the United States, Europe, and Asia.
Through these collaborations, students can learn how computational predictions guide experiments and how combined theoretical–experimental studies develop into internationally competitive publications.
Explore chemical spaces that cannot be searched through conventional trial-and-error approaches.
Research topics include:
Machine-learning prediction of molecular and materials properties
Generative and evolutionary design of new materials
High-throughput screening of millions to billions of candidates
Explainable AI for structure–property relationships
Autonomous optimization of energy materials
Design electrode materials with higher energy density, improved stability, and new charge-storage mechanisms.
Research topics include:
Organic and inorganic electrode materials
Multielectron redox reactions
Electrolyte–electrode interactions
Ion insertion and diffusion
AI-assisted discovery of battery materials
Understand catalytic mechanisms at the atomic scale and design more active and durable catalysts.
Research topics include:
Hydrogen evolution reaction
Oxygen evolution reaction
Defect and vacancy engineering
Two-dimensional catalysts
Single-atom and transition-metal catalysts
Catalyst stability under realistic reaction conditions
Connect molecular-level interactions with macroscopic material and process performance.
Research topics include:
Gas adsorption and separation
Porous materials and molecular transport
Grand canonical Monte Carlo simulations
Molecular dynamics
Process-level performance prediction
Build a strong foundation in computational chemistry, materials science, and scientific programming.
Develop an original research question and generate results using advanced simulations and AI.
Transform your results into a complete scientific story and an international journal publication.
Grow into an independent researcher who can design projects, collaborate across disciplines, and communicate scientific ideas effectively.
Previous experience in DFT, molecular simulation, or machine learning is an advantage but is not required for graduate applicants. Motivation, intellectual curiosity, and the willingness to learn are more important.
Financial support (KRW 1.5–2.0 million per month) for eligible full-time graduate students
Direct research mentoring from the principal investigator
Access to high-performance computing and AI infrastructure
Participation in major government-funded research projects
Opportunities for first-author publications in high-impact journals
Domestic and international research collaborations
Support for conference presentations and professional development
Guidance throughout admission, visa, and settlement procedures
Financial support and its detailed conditions depend on the applicant’s position, qualifications, admission status, and applicable funding regulations.
We welcome applicants with backgrounds in:
Chemical Engineering
Materials Science and Engineering
Chemistry
Physics
Energy Engineering
Computer Science
Artificial Intelligence
Related scientific and engineering disciplines
Strong candidates should demonstrate:
Genuine interest in computational materials research
Curiosity about energy and sustainability challenges
Willingness to learn programming and simulation methods
Ability to communicate and collaborate
Commitment to developing research into peer-reviewed publications
Konkuk University’s application period for Spring 2027 graduate admission is:
September 30–October 20, 2026
Prospective applicants are strongly encouraged to contact Prof. Kim before submitting the university application so that research interests, funding availability, and admission requirements can be discussed in advance.
Please email the following materials to Prof. Ki Chul Kim:
Email: kich2018@konkuk.ac.kr
Subject: [CMD Lab Application] Position – Full Name
Curriculum vitae
Undergraduate and graduate transcripts, if applicable
Brief description of research interests
English proficiency information, if available
Curriculum vitae
Publication list
Two or three representative publications
Brief research proposal or statement of research interests
Shortlisted applicants will be invited to an online interview.
CMD Lab is looking for researchers who want to do more than operate computational software. We seek people who want to understand materials, discover new scientific principles, and develop ideas that can shape the future of energy technology.
If you are ready to combine computation, chemistry, and AI to discover better materials, we would be pleased to hear from you.