Adjunct Assistant Scientist in AI-Driven Discovery
2 weeks ago
Adjunct Assistant Scientist in AI-Driven Discovery in Chemistry
About the Position:We are seeking a highly skilled computational chemist to join our team as an Adjunct Assistant Scientist in AI-Driven Discovery in Chemistry. The successful candidate will work on a project led by Dr. Mingjie Liu in the Department of Chemistry, focusing on the development of Machine Learning Interatomic Potentials (MLIPs) and their applications in computational chemistry.
Key Responsibilities:- Develop MLIPs and apply uncertainty quantification (UQ) and active learning (AL) methods to improve their performance.
- Conduct density functional theory (DFT) and molecular dynamics simulations to explore materials properties.
- Work on cutting-edge projects involving 2D and 3D structure prediction and property exploration for materials, including hydrogen storage and other applications.
- PhD in chemistry, materials science, physics, or a related field.
- Postdoctoral research experience in related areas is highly preferred.
- Strong publication record in peer-reviewed journals in materials modeling, MLIP development, and computational chemistry.
- Experience with data-driven approaches in materials discovery and design.
- Proficiency in UQ and AL techniques.
- Expertise in data preparation, analysis, and familiarity with structure prediction algorithms.
To be considered for this position, please submit a complete application, including a letter of application, a complete curriculum vitae, a statement on research goals, and a list of at least three references. Applications will be reviewed beginning October 8, and the position will remain open until filled.
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