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PostDoc: Machine Learning: Interatomic Potential ... (No replies)
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Postdoctoral Research Associate in Machine Learning-Assisted Materials Simulation
Organization: Artificial Intelligence for Science Institute (AISI)
AISI is a new research institute in Beijing, China. AISI’s mission is to boost scientific research with artificial intelligence by integrating academic and engineering efforts. AISI welcomes people from anywhere in the world who are excited by the idea of using AI to do better science.
Job title: Postdoctoral Research Associate
Working language: English
Job description:
Full-time positions are available in the AISI molecular simulation group, effective immediately. The research focuses on the development of potential energy surfaces/interatomic potentials using deep learning methods for atomistic simulations for computational materials science. In particular, the project will focus on the development of a broad spectrum of deep learning interatomic potential models for metals and alloys for the world materials science community (the same methodology will be applied to semiconductors, battery materials, …). The development activity will focus on a broad set of materials properties, including thermodynamic, mechanical, and defect properties, at the accuracy of electronic structure-based calculations. The postdoctoral research associate will work with Professor Weinan E (AISI, Princeton) and be jointly supervised by Professor David J. Srolovitz (Hong Kong Institute for Advanced Study) along with other AISI Staff. The positions will be based at AISI in Beijing but frequent trips to Hong Kong, where Prof. Srolovitz, is based are expected. The positions are for two years with the possibility for renewal. Salary and benefits are competitive and will be commensurate with the qualification of the candidate.
The candidate shall possess:
A Ph.D. degree in materials science or related fields in physics, mechanics of materials, chemistry or applied mathematics;
Excellent publication track record in related fields and a demonstrated commitment to excellence;
Experience in first-principles calculations and molecular dynamics simulations;
Proficient programming skills in python, C++, and bash scripts;
Experience in machine learning frameworks or GPU CUDA/OpenCL development is a plus;
Ability to work independently and within a team; and
Excellent skills in written and oral communication are essential.
To apply, please forward your CV and contact information for three referees to Dr. Linfeng Zhang ([email protected]).