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6 days ago
The successful candidate will join a multidisciplinary research group to advance knowledge in AI-accelerated discovery and design of porous materials for energy and environmental applications.
- Develop and apply machine learning models to predict structural and electronic properties of nanoporous materials.
- Construct and expand curated databases by integrating text mining, graph theory, and computational chemistry outputs.
- Perform high-throughput computational screening of porous materials for applications such as gas adsorption, separation, and catalysis.
- Enhance the accuracy and efficiency of molecular simulations by coupling AI models with quantum chemical calculations.
- Publish research findings in high-impact journals and present at leading international conferences.
- Contribute to proposal writing and assist in preparing funding applications in support of research activities.
Requirements include:
- A PhD in Chemistry, Materials Science, Chemical Engineering, Physics, Computational Science, or a related discipline.
- A strong background in nanoporous materials and structure-property relationships.
- A proven research track record, evidenced by publications in peer-reviewed journals.
- Excellent communication skills and a strong interest in interdisciplinary collaboration.
Desirable skills include expertise in computational materials science, including density functional theory, molecular simulations, and multi-scale modeling. Strong programming skills are also required, with experience in ML frameworks such as PyTorch and TensorFlow.
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