In our lab,
we develop novel materials for energy and environmental related applications
using computational modeling and big-data analysis. We are looking to hire for
postdoctoral researchers with a strong interest in the following research
Multi-scale computational modeling for nanoporous materials (e.g. zeolites,
metal organic frameworks) for gas storage / gas separation applications.
ii. Application of machine learning in materials
science, including the development of artificial neural network (ANN)
potentials and material prediction by machine leaning.
1. Applicants are required to have a doctoral
degree (Ph.D.) in one of the following majors: chemical engineering, materials
science, chemistry or related fields.
2. Experiences of computational modeling (using
DFT, MD, MC, and so on), computational algorithms development, and coding
experiences will be advantageous.
3. We are especially interested in those who are
experienced in machine learning algorithm or in the development of the
artificial neural network (ANN) potential.
4. Excellent communication and writing skills in English are required.
Main responsibilities include, but are not limited to:
1. Carry out research projects independently as well as a part of a team.
2. Help with the student supervision and education.
We invite qualified and highly motivated candidates to email (all in English) a
full CV, together with a summary of research interests to firstname.lastname@example.org, cc to email@example.com