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 David J. Srolovitz
Materials Theory and Computation Group
The University of Hong Kong

Join our group

Thank you for your interest in working with our group. Our research interests are interdisciplinary ranging from materials theory particularly defects, grain boundaries, phase transformations, opto-electronic properties, development of machine learning potentials, artificial intelligence driven discovery of high entropy alloys, and statistical thermodynamics theories of materials.

Motivated PhD students, postdocs, exchange students from mainland China and collaborators can find information on how to join our group or collaborate with members of our group below.


Contact Us:

Please contact Professor David Srolovitz through email at , Dr. Subrahmanyam Pattamatta at , and Dr. Tongqi Wen at . You can also contact any of our group members to know more about the research in our group, work culture, etc before you take a decision to apply for a position or collaborate with us.


Our Laboratory
Materials Theory and Computation Group
Department of Mechanical Engineering
Room MW104, First Floor
Meng Wah Complex
The University of Hong Kong
Pokfulam Road
Hong Kong

PhD Students: Multiple positions available

We are currently looking for PhD students to work on the following projects:

  • Development of machine learning potentials for defect properties
  • Artificial intelligence driven discovery of high-entropy alloy (HEA) with targeted thermo-elastic and magnetic properties
  • Atomistic simulations of defect properties in Ti-based alloys and HEA
  • Grain boundary models

Exchange Students/Scholars from Mainland China: Multiple positions available

Exchange students from mainland China are always welcome to work on the following projects:

  • Development of machine learning potentials
  • Development of workflows for open-source community
  • Artificial intelligence driven discovery of high-entropy alloy (HEA) with targeted thermo-elastic and magnetic properties
  • Atomistic simulations of defect properties in Ti-based alloys and HEA
  • High performance computing + AI

Postdoctoral Fellows: available

We encourage interested candidates to apply for RGC Postdoctoral Fellowship Scheme to work on the following projects:

  • Development of machine learning potentials for defect properties
  • Artificial intelligence driven discovery of high-entropy alloy (HEA) with targeted thermo-elastic and magnetic properties
  • Atomistic simulations of defect properties in Ti-based alloys and HEA

Collaborators: Always welcome

Please contact us.